bluuebunny/crossref_metadata_2025 huggingface dataset:
Proteomic identification of early urinary-biomarkers of acute kidney injury in preterm infants
Authors: Jung Young Hwa , Han Dohyun , Shin Seung Han , Kim Ee-Kyung , Kim Han-Suk
Published: March 2020

The immature preterm kidney is likely to be vulnerable to acute kidney injury (AKI). However, the biomarkers currently used for AKI are not sensitive or specific and are also inadequate for the timely detection of AKI in preterm infants. The objectives of this study were to identify novel urinary biomarkers of AKI using proteomic techniques, and to verify and validate that the candidates can serve as early predictive biomarkers for AKI. In total, 1,810 proteins were identified in the discovery phase. Among those proteins, 174 were selected as the 1st targeted proteins. A total of 168 proteins were quantified, and the levels of 6 were significantly increased in the AKI group in the verification phase. Using a clinical assay, the results were confirmed and validated using samples of the first urine after birth from the biorepository. Finally, enzyme-linked immunosorbent assays revealed that the levels of annexin A5, neutrophil gelatinase-associated lipocalin (NGAL), and protein S100-P were significantly higher in the samples of the first urine from patients with AKI than in those from patients without AKI. In conclusion, urinary annexin A5, NGAL and protein S100-P levels are promising biomarkers for early, accurate prediction of AKI in preterm infants.
Surface distortion of Fe dot-decorated TiO2 nanotubular templates using time-of-flight grazing incidence small angle scattering
Authors: Paul Neelima , Moulin Jean-Francóis , Mangiapia Gaetano , Kriele Armin , Müller-Buschbaum Peter , Opel Matthias , Paul Amitesh
Published: March 2020

Physical properties of nanoclusters, nanostructures and self-assembled nanodots, which in turn are concomitantly dependent upon the morphological properties, can be modulated for functional purposes. Here, in this article, magnetic nanodots of Fe on semiconductor TiO2 nanotubes (TNTs) are investigated with time-of-flight grazing incidence small-angle neutron scattering (TOF-GISANS) as a function of wavelength, chosen from a set of three TNT templates with different correlation lengths. The results are found corroborating with the localized scanning electron microscopy (SEM) images. As we probe the inside and the near-surface region of the Fe-dotted TNTs with respect to their homogeneity, surface distortion and long-range order using TOF-GISANS, gradual aberrations at the top of the near-surface region are identified. Magnetization measurements as a function of temperature and field do not show a typical ferromagnetic behavior but rather a supermagnetic one that is expected from a nonhomogeneous distribution of Fe–dots in the intertubular crevasses.
Author Correction: MIG1 as a positive regulator for the histidine biosynthesis pathway and as a global regulator in thermotolerant yeast Kluyveromyces marxianus
Authors: Nurcholis Mochamad , Murata Masayuki , Limtong Savitree , Kosaka Tomoyuki , Yamada Mamoru
Published: March 2020

An amendment to this paper has been published and can be accessed via a link at the top of the paper.
Complete Profiling of Methyl-CpG-Binding Domains for Combinations of Cytosine Modifications at CpG Dinucleotides Reveals Differential Read-out in Normal and Rett-Associated States
Authors: Buchmuller Benjamin C. , Kosel Brinja , Summerer Daniel
Published: March 2020

5-Methylcytosine (mC) exists in CpG dinucleotides of mammalian DNA and plays key roles in chromatin regulation during development and disease. As a main regulatory pathway, fully methylated CpG are recognized by methyl-CpG-binding domain (MBD) proteins that act in concert with chromatin remodelers, histone deacetylases and methyltransferases to trigger transcriptional downregulation. In turn, MBD mutations can alter CpG binding, and in case of the MBD protein MeCP2 can cause the neurological disorder Rett syndrome (RTT). An additional layer of complexity in CpG recognition is added by ten-eleven-translocation (TET) dioxygenases that oxidize mC to 5-hydroxymethyl-, 5-formyl- and 5-carboxylcytosine, giving rise to fifteen possible combinations of cytosine modifications in the two CpG strands. We report a comprehensive, comparative interaction analysis of the human MBD proteins MeCP2, MBD1, MBD2, MBD3, and MBD4 with all CpG combinations and observe individual preferences of each MBD for distinct combinations. In addition, we profile four MeCP2 RTT mutants and reveal that although interactions to methylated CpGs are similarly affected by the mutations, interactions to oxidized mC combinations are differentially affected. These findings argue for a complex interplay between local TET activity/processivity and CpG recognition by MBDs, with potential consequences for the transcriptional landscape in normal and RTT states.
The Effect of Eucalyptol on Nursing Home Residents
Authors: Goto Seiko , Suzuki Hinako , Nakagawa Toshinori , Shimizu Kuniyoshi
Published: March 2020

Eucalyptol is one of the most popular volatile components. It is used in many essential oils for relieving sinus and lung congestion caused by a variety of conditions. This pilot study sought to analyze clinical evidence for the effect of the scent of eucalyptol on the cognitive function of elderly people. Seventy nursing-home residents with cognitive impairment were recruited. Three one-week experiments were performed: eucalyptol scent was diffused in bedrooms with a diffuser only at wake-up time in the first experiment, and at wake-up time and bedtime in the second and third experiments. Results showed that although an improvement was not seen when using Mini Mental State Examination (MMSE) and Cohen-Mansfild Agitation Inventory (CMAI) measures, Dementia Behavior Disturbance Scale (DBD) scores improved significantly, even though no subject reported perceiving the scent. The significant improvements of the behaviour were found not only among the subjects whose room had a diffuser but also among the subjects who were exposed to an unperceivable level of eucalyptol drifted in the living room.
Immunotherapeutic potential of CD4 and CD8 single-positive T cells in thymic epithelial tumors
Authors: Yamamoto Yoko , Iwahori Kota , Funaki Soichiro , Matsumoto Mitsunobu , Hirata Michinari , Yoshida Tetsuya , Kanzaki Ryu , Kanou Takashi , Ose Naoko , Minami Masato , Sato Eiichi , Kumanogoh Atsushi , Shintani Yasushi , Okumura Meinoshin , Wada Hisashi
Published: March 2020

Indications for current immune checkpoint inhibitors are expanding and now include thymic epithelial tumors (TETs). Although clinical trials on immune checkpoint inhibitors for TETs are ongoing, a rationale has not yet been established for immunotherapy for TETs. Therefore, we herein performed phenotypic and functional analyses of T cells in surgically resected TET tissues with a focus on the anti-tumor properties of T cells to TETs as a step towards establishing a rationale for immunotherapy for TETs. We examined T-cell profiles in surgically resected TET tissues, particularly CD4 and CD8 single-positive T cells, using flow cytometry. In the functional analysis of T cells in TETs, we investigated not only cytokine production by T cells, but also their cytotoxicity using bispecific T-cell engager technology. The cluster analysis of T-cell profiles based on flow cytometric data revealed that type B3 thymoma and thymic carcinoma (B3/C) belonged to the hot cluster characterized by a high proportion of Tim-3+ and CD103+ in CD4 and CD8 single-positive T cells. Enhancements in cytokine production and the cytotoxicity of T cells by the anti-PD-1 antibody were significantly greater in B3/C. These results indicate the potential of immunotherapy for patients with B3/C.
The First 250 ms of Auditory Processing: No Evidence of Early Processing Negativity in the Go/NoGo Task
Authors: Fogarty Jack S. , Barry Robert J. , Steiner Genevieve Z.
Published: March 2020

Past evidence of an early Processing Negativity in auditory Go/NoGo event-related potential (ERP) data suggests that young adults proactively process sensory information in two-choice tasks. This study aimed to clarify the occurrence of Go/NoGo Processing Negativity and investigate the ERP component series related to the first 250 ms of auditory processing in two Go/NoGo tasks differing in target probability. ERP data related to each task were acquired from 60 healthy young adults (M = 20.4, SD = 3.1 years). Temporal principal components analyses were used to decompose ERP data in each task. Statistical analyses compared component amplitudes between stimulus type (Go vs. NoGo) and probability (High vs. Low). Neuronal source localisation was also conducted for each component. Processing Negativity was not evident; however, P1, N1a, N1b, and N1c were identified in each task, with Go P2 and NoGo N2b. The absence of Processing Negativity in this study indicated that young adults do not proactively process targets to complete the Go/NoGo task and/or questioned Processing Negativity’s conceptualisation. Additional analyses revealed stimulus-specific processing as early as P1, and outlined a complex network of active neuronal sources underlying each component, providing useful insight into Go and NoGo information processing in young adults.
Author Correction: Differential immune response modulation in early Leishmania amazonensis infection of BALB/c and C57BL/6 macrophages based on transcriptome profiles
Authors: Aoki Juliana Ide , Muxel Sandra Marcia , Zampieri Ricardo Andrade , Müller Karl Erik , Nerland Audun Helge , Floeter-Winter Lucile Maria
Published: March 2020

An amendment to this paper has been published and can be accessed via a link at the top of the paper.
From single to a dual-gene delivery nanosystem: coordinated expression matters for boosting the neovascularization in vivo
Authors: Gao Bin , Wang Xiaoyu , Wang Meiyu , Ren Xiang-kui , Guo Jintang , Xia Shihai , Zhang Wencheng , Feng Yakai
Published: March 2020

A dual-gene delivery system with coordinated expression function boosted the neovascularization.
Comment on “Effect of Montmorency tart cherry juice on cognitive performance in older adults: a randomized controlled trial” by S. C. Chai, J. Jerusik, K. Davis, R. S. Wright and Z. Zhang, Food Funct., 2019, 10, 4423–4431
Authors: Heston Thomas F.
Published: March 2020

The article looking at the effect of Montmorency tart cherry juice supplementation on 50 to 80 years old people with normal cognitive function concluded that supplementation may improve cognitive functioning.
Enzymatic cross-linking of pectin in a high-pressure foaming process
Authors: Wemmer Judith , Holtgrave Sarah , Wiest Laura , Michel Martin , Leser Martin E. , Windhab Erich J.
Published: March 2020

This study demonstrates that integrating enzymatic cross-linking in a high-pressure foaming process is a viable option to increase foam stability when well aligning the relevant process parameters and process kinetics.
N-Acylphosphatidylethanolamines andN-acylethanolamines increase in saliva upon food mastication: the influence of the individual nutritional status and fat type in food
Authors: De Luca Lucia , Ferracane Rosalia , Calderón Ramírez Nancy , Vitaglione Paola
Published: March 2020

SalivaryN-acylphosphatidylethanolamines andN-acylethanolamines are more abundant in obese subjects than in normal weight subjects and they increase upon mastication depending on the fat type in food.
Multiscale optimization of Li-ion diffusion in solid lithium metal batteries via ion conductive metal–organic frameworks
Authors: Zhang Qi , Li Dixiong , Wang Jia , Guo Sijia , Zhang Wei , Chen Dong , Li Qi , Rui Xianhong , Gan Liyong , Huang Shaoming
Published: March 2020

Optimization of solid electrolytes (SEs) is of great significance for lithium-based solid state batteries (SSBs).
Tunable swelling and deswelling of temperature- and light-responsive graphene oxide-poly(N-isopropylacrylamide) composite hydrogels
Authors: Li Minghao , Bae Jinhye
Published: March 2020

Swelling and deswelling behaviors of graphene oxide-poly(N-isopropylacrylamide) composite hydrogels can be tuned by the concentrations of a chemical crosslinker and graphene oxide, and the rate of the external temperature change.
An additional potential donor-bearing alkylidene-containing latent NHC–ruthenium-based catalyst for olefin metathesis polymerization
Authors: Sivanesan Dharmalingam , Seo Bongkuk , Lim Choong-Sun , Choi Dongchen , Kim Taehee , Kim Hyeon-Gook
Published: March 2020

Introduction of an additional donor, by tethering substituted pyridine, in the alkylidene ligand of a NHC-based ruthenium complex initiates latent olefin metathesis polymerization.
Self-division of giant vesicles driven by an internal enzymatic reaction
Authors: Miele Ylenia , Medveczky Zsófia , Holló Gábor , Tegze Borbála , Derényi Imre , Hórvölgyi Zoltán , Altamura Emiliano , Lagzi István , Rossi Federico
Published: March 2020

Giant unilamellar vesicles having pH-sensitive bilayers can undergo self-division triggered by an internal enzymatic (urea–urease) reaction coupled to a cross-membrane transport of the chemical species.
Effects of topological constraints on linked ring polymers in solvents of varying quality
Authors: Ahmadian Dehaghani Zahra , Chubak Iurii , Likos Christos N. , Ejtehadi Mohammad Reza
Published: March 2020

We investigate the effects of topological constraints in catenanes composed of interlinked ring polymers on their size in a good solvent as well as on the location of theirθ-point when the solvent quality is worsened.
Substrate curvature governs texture orientation in thin films of smectic block copolymers
Authors: Nielsen Bjarke Frost , Linga Gaute , Christensen Amalie , Mathiesen Joachim
Published: March 2020

An effective field theory of finite-thickness block copolymer films shows how curvature can control texture formation.
Red luminescent Eu2+ in K2MgH4 and comparison with KMgH3
Authors: Ueda Jumpei , Wylezich Thomas , Kunkel Nathalie , Tanabe Setsuhisa
Published: March 2020

A Ruddlesden–Popper (n = 1) hydride perovskite, K2MgH4:Eu2+, shows longer wavelength luminescence compared with the KMgH3:Eu2+ simple perovskite by crystal field engineering.
Isolated asymmetric bilateral steric conjugated polymers with thickness-independent emission for efficient and stable light-emitting optoelectronic devices
Authors: Sun Ning , Liu Yuqin , Sun Lili , Han Yamin , An Xiang , Xu Man , Sun Chen , Lin Jinyi , Bai Lubing , Li Bo , Wei Chuanxin , Yin Chengrong , Yu Mengna , Wei Qi , Ding Xuehua , Lin Zongqiong , Liu Yuyu , Guo Dong , Zhang Xinwen , Xie Linghai , Huang Wei
Published: March 2020

Isolating the mainchain of light-emitting conjugated polymers (LCPs) is an effective strategy to obtain ultrastable efficient deep-blue light-emitting devices for printed optoelectronics.
Correction: Applications of Raman spectroscopy in the development of cell therapies: state of the art and future perspectives
Authors: Rangan Shreyas , Schulze H. Georg , Vardaki Martha Z. , Blades Michael W. , Piret James M. , Turner Robin F. B.
Published: March 2020

Correction for ‘Applications of Raman spectroscopy in the development of cell therapies: state of the art and future perspectives’ by Shreyas Rangan et al., Analyst, 2020, DOI: 10.1039/c9an01811e.
A DNA tweezers-actuated regenerated DNAzyme nanoreactor: a fluorescence sensor for miRNA and adenosine detection
Authors: Chen Xueying , Fu Xinrui , Wu Yuanyu , Jin Yifan , Li Wei
Published: March 2020

A DNA tweezers-actuated controllable and regulatable DNAzyme nanoreactor was developed for cancer-related miRNA and adenosine detection.
Fast immunoassay for microfluidic western blotting by direct deposition of reagents onto capture membrane
Authors: Arvin Natalie E. , Dawod Mohamed , Lamb Don T. , Anderson Jon P. , Furtaw Michael D. , Kennedy Robert T.
Published: March 2020

To further improve the speed and miniaturization of a complete Western blot, a microscale immunoassay with direct deposition of immunoassay reagents has been developed with the flow deposition of antibodies.
A tetranuclear cobalt(ii) phosphate possessing a D4R core: an efficient water oxidation catalyst
Authors: Dey Atanu , Kumar Vierandra , Pal Shubhadeep , Guha Anku , Bawari Sumit , Narayanan Tharangattu N. , Chandrasekhar Vadapalli
Published: March 2020

A tetranuclear CoII-phosphate has been found to be an efficient water oxidation catalyst.
Direct imaging of heteroatom dopants in catalytic carbon nano-onions
Authors: Thomas Melonie P. , Wanninayake Namal , De Alwis Goonatilleke Manisha , Kim Doo Young , Guiton Beth S.
Published: March 2020

Direct visualization of dopant atom configuration in carbon nano-onions provides structure–property link to catalytic activity.
Gold nanoclusters as electrocatalysts: size, ligands, heteroatom doping, and charge dependences
Authors: Kumar Bharat , Kawawaki Tokuhisa , Shimizu Nobuyuki , Imai Yukari , Suzuki Daiki , Hossain Sakiat , Nair Lakshmi V. , Negishi Yuichi
Published: March 2020

Results of this study provide clear design guidelines for developing highly active electrocatalysts using thiolate-protected gold and alloy clusters.
Undercooling-directed NaCl crystallization: an approach towards nanocavity-linked graphene networks for fast lithium and sodium storage
Authors: Chen Yaxin , Shi Liluo , Li Da , Dong Yue , Yuan Qiong , Huang Shaozhuan , Yang Hui Ying , Wei Xianyong , Zhuang Quanchao , Ju Zhicheng , Song Huaihe
Published: March 2020

Despite the crystallization of inorganic salts being technologically related to the fabrication of salt-templated materials, the two key steps, nucleation and crystal growth, still lack the kinetic control to enable precise design of salt scaffolds.
β-Carboline directed regioselective hydroxylation by employing Cu(OAc)2 and mechanistic investigation by ESI-MS
Authors: Bora Darshana , Tokala Ramya , John Stephy Elza , Prasanth Bitla , Shankaraiah Nagula
Published: March 2020

This protocol demonstrates microwave-irradiated monohydroxylation on different heterocycles via C–H functionalization which leads into the development of biologically relevant molecules.
High-performance n- and p-type organic single-crystal field-effect transistors with an air-gap dielectric towards anti-ambipolar transport
Authors: Liu Jianghong , Liu Jie , Zhang Jing , Li Chunlei , Cui Qiuhong , Teng Feng , Li Hongxiang , Jiang Lang
Published: March 2020

By combining high-performance n- and p-type single crystals with an air-gap dielectric, excellent anti-ambipolar transport with a small hysteresis was achieved.
Nobiletin exerts anti-diabetic and anti-inflammatory effects in anin vitrohuman model andin vivomurine model of gestational diabetes
Authors: Nguyen-Ngo Caitlyn , Salomon Carlos , Quak Stephanie , Lai Andrew , Willcox Jane C , Lappas Martha
Published: March 2020

Gestational diabetes mellitus (GDM) is a global health issue, whereby pregnant women are afflicted with carbohydrate intolerance with first onset during pregnancy. GDM is characterized by maternal peripheral insulin resistance, thought to be driven by low-grade maternal inflammation. Nobiletin, a polymethoxylated flavonoid, possesses potent glucose-sensitizing and anti-inflammatory properties; however, its effects in GDM have not been assessed. The present study aimed to determine the effects of nobiletin on glucose metabolism and inflammation associated with GDM in both in vitro human tissues and an in vivo animal model of GDM. In vitro, treatment with nobiletin significantly improved TNF-impaired glucose uptake in human skeletal muscle, and suppressed mRNA expression and protein secretion of pro-inflammatory cytokines and chemokines in human placenta and visceral adipose tissue (VAT). Mechanistically, nobiletin significantly inhibited Akt and Erk activation in placenta, and NF-κB activation in VAT. In vivo, GDM mice treated with 50 mg/kg nobiletin daily via oral gavage from gestational day (gd) 1-17 or via i.p. injections from gd 10-17 significantly improved glucose tolerance. Pregnant GDM mice treated with nobiletin from either gd 1-17 or gd 10-17 exhibited significantly suppressed mRNA expression of pro-inflammatory cytokines and chemokines in placenta, VAT and subcutaneous adipose tissue (SAT). Using a quantitative mass spectrometry approach, we identified differentially abundant proteins associated with the effect of nobiletin in vivo. Together, these studies demonstrate that nobiletin improves glucose metabolism and reduces inflammation associated with GDM and may be a novel therapeutic for the prevention of GDM.
Music genre classification and music recommendation by using deep learning
Authors: Elbir A. , Aydin N.
Published: March 2020

Today, music is a very important and perhaps inseparable part of people's daily life. There are many genres of music and these genres are different from each other, resulting in people to have different preferences of music. As a result, it is an important and up‐to‐date issue to classify music and to recommend people new music in music listening applications and platforms. Classifying music by their genre is one of the most useful techniques used to solve this problem. There are a number of approaches for music classification and recommendation. One approach is based on the acoustic characteristics of music. In this study, a music genre classification system and music recommendation engine, which focuses on extracting representative features that have been obtained by a novel deep neural network model, have been proposed. Acoustic features extracted from these networks have been utilised for music genre classification and music recommendation on a data set.
Machine learning‐driven protein engineering: a case study in computational drug discovery
Authors: Rickerby Harry F. , Putintseva Katya , Cozens Christopher
Published: March 2020

Research and development in drug discovery will need to find significant efficiency gains if the industry is to continue generating novel drugs. There is great expectation for machine learning (ML) to provide this boost in R&D productivity, but to harness the full potential of ML, the generation of new, high‐quality datasets will be necessary. Here, the authors present a platform that combines high‐throughput display and selection data generation with ML. More specifically, deep learning is used to inform the directed evolution of novel biotherapeutics using DNA library synthesis, ultra‐high throughput selections, and next generation sequencing. By combining the learnings of multiple in silico models, their platform enables multi‐parameter optimisation across multiple important protein characteristics. They also present a model for benchmarking these ML‐driven drug discovery platforms according to the accuracy of their underlying in silico models, in conjunction with the throughput of their empirical experimentation.
Optimal control and stabilisation for large‐scale systems with imposed constraints
Authors: Qi Qingyuan , Ju Peijun , Zhang Huanshui , Cui Peng
Published: March 2020

This study mainly concerns the linear quadratic optimal control and stabilisation problems for large‐scale systems with constraint, the constraint is imposed on the weighted control and state, which arises from coordination problem for multi‐agent systems. The main contributions of this study are: first, the optimal controller is developed via using the maximum principle and decoupling the forward and backward difference equations (FBDEs); secondly, by defining the Lyapunov function with the optimal cost function, the necessary and sufficient stabilisation conditions for the large‐scale systems are derived. The main techniques adopted in this study are the maximum principle and the solution to the FBDEs. It is noted that the optimal control strategy involves the centralised information of the weighted state average, but this can be easily accessed for the large‐scale‐system network.
Stabilisation of networked control systems under a novel stochastic‐sampling‐based adaptive event‐triggered scheme
Authors: Xie Xuhuan , Li Shanbin , Xu Bugong
Published: March 2020

In order to save the usage of system resources and adapt the variation of plant state, this study first proposes a novel stochastic‐sampling‐based adaptive event‐triggered scheme (AETS). Second, in the framework of time‐delay systems, the closed‐loop control system is modelled as a class of delayed stochastic systems where time‐delay is distributed in some intervals with probability. Then, by employing stochastic analysis tool and Lyapunov stability theory, a stability criterion for this class of delayed stochastic systems is established to ensure that the system possesses stochastically asymptotic stability with an disturbance attenuation performance. Also, a co‐design of parameter matrices of the state‐feedback controller and the stochastic‐sampling‐based AETS is implemented. Third, based on the obtained co‐design condition, a convex optimisation algorithm for the tradeoffs between disturbance attenuation performance and resource utilisation of the closed‐loop control system is further developed. Finally, the effectiveness and feasibility of the proposed control strategy are illustrated by two numerical examples of adaptive event‐triggered control for networked control systems under stochastic sampling.
Improved conditions for event‐triggered control of switched linear systems
Authors: Wang Yue‐E , Wu Di , Niu Ben
Published: March 2020

The sampled‐data event‐triggered control problem of switched linear systems in which both the sampled information of the system states and the switching signal are available to the controller at the event‐triggered transmission instants is studied here. The coexistence of the event‐triggered transmission and the switching behaviour makes the switching signal of the controller and the switching signal of the system asynchronous. By constructing a new multiple Lyapunov–Krasovskii functional and using the asynchronous switching method, the exponential stability conditions characterised by mode‐dependent average dwell time of the switching signal are proposed. Then, the corresponding solvability conditions for the event‐triggered state feedback controller are formulated. Finally, a numerical example is given to illustrate the validity of the proposed results.
Robust delay‐dependent LPV synthesis for blood pressure control with real‐time Bayesian parameter estimation
Authors: Tasoujian Shahin , Salavati Saeed , Franchek Matthew A. , Grigoriadis Karolos M.
Published: March 2020

Mean arterial blood pressure (MAP) dynamics estimation and its automated regulation could benefit the clinical resuscitation of patients in critical conditions. To address the variability and complexity of the MAP response of patients to vasoactive drug infusion, a parameter‐varying model with a varying delay is considered to describe such dynamics. The estimation of the varying parameters and delay is performed via a Bayesian‐based multiple‐model square‐root cubature Kalman filtering (MMSRCKF) approach. The estimation results substantiate the effectiveness of the utilized identification method using experimental data. Next, an automated drug delivery scheme to regulate the real‐time MAP response of patients is developed via time‐delay linear parameter‐varying (LPV) control techniques. To this end, a gain‐scheduled outputfeedback LPV controller is designed to track a desired reference MAP target and guarantee robustness against norm‐bounded uncertainties and disturbances in terms of the closed‐loop system induced ‐norm. Parameter‐dependent Lyapunov–Krasovskii functionals (LKFs) are used to derive sufficient conditions in the convex linear matrix inequality (LMI) constraint framework for the robust stabilization of LPV systems with arbitrarily varying delay. Finally, to evaluate the performance of the proposed MAP regulation approach, closed‐loop simulations are conducted, and the results confirm the effectiveness of the proposed method against various simulated clinical scenarios.
Family of controllers based on sector non‐linear functions: an application for first‐order dynamical systems
Authors: Meza‐Sánchez Marlen , Rodríguez‐Liñán Maria del Carmen , Clemente Eddie
Published: March 2020

This study proposes the design of a family of controllers based on sector non‐linear functions for first‐order dynamical systems. Three new controllers that incorporate these types of functions are presented and analysed to validate the authors' premise. The proposed nominal controllers and an augmented version with integral action are presented. Asymptotic stability is proven under the Lyapunov theory and the controllers' performance is compared against a traditional proportional controller. An empirically tuned relation depending on a constant bound value and an operation range is proposed; this is used to compute the gains of each controller. Simulation results with all of the controllers under saturation bounds are presented to illustrate the effectiveness of the method at solving the output regulation and the tracking control problems, under practical physical assumptions. The numerical comparison utilises the and norms over the output error, and over the control variable, applying the same saturation bounds for each controller.
Finite‐time bounded stabilisation for linear systems with finite‐time H2 ‐gain constraint
Authors: Zhang Shuai , Guo Yang , Wang Shicheng , Liu Zhiguo , Hu Xiaoxiang
Published: March 2020

This study discusses the finite‐time boundedness (FTB) of the state of linear systems with a finite‐time H2 ‐gain performance constraint. With time‐varying exogenous disturbances, the sufficient conditions for linear time‐invariant and linear time‐varying systems to satisfy both the FTB constraint and the finite‐time H2 ‐gain performance constraint are developed. On the basis of the matrix inequality theory, a method for designing a controller by using state feedback is derived for each of the two classes of linear systems. These methods can effectively keep the state from reaching an unacceptable value and modulate the output performance within a specified finite‐time interval. Two application examples of the terminal guidance scenario verify the effectiveness of the proposed methods.
Adaptive non‐singular fast terminal sliding mode control for multi‐agent systems with unknown non‐linear dynamics
Authors: Gu Xiaowei , Niu Yugang , Chen Bei
Published: March 2020

This study considers the finite time consensus tracking problems for second‐order non‐linear multi‐agent system with the unknown dynamics. Firstly, the radial basis function neural networks are utilised to approximate the lumped unknown dynamic model. And then, to achieve the finite‐time consensus tracking, a distributed non‐singular fast terminal sliding mode control strategy is designed which can speed up the convergence of the multi‐agent system. Moreover, the consistency under the proposed control strategy is theoretically analysed and the upper bound of setting time is explicitly obtained. Finally, two simulation examples are provided.
Novel distortion free and histogram based data hiding scheme
Authors: Aghababaiyan Keyvan , Mortazavi Amir S.
Published: March 2020

In the most data hiding methods, the cover media is entirely distorted and it cannot be recovered when the secretive data is extracted. However, in some applications, such as medical imaging, military imaging and law enforcement, even a slight modification in the cover image is impermissible. Therefore, reversible data hiding schemes have proposed as a solution of this issue, recently. Histogram based embedding schemes are among wide investigated reversible data hiding schemes owing to the high quality of the marked images. In histogram based embedding techniques, construction of histogram greatly affects the embedding capacity and the distortion performance of schemes. In this study, the authors propose a novel reversible data hiding scheme for grey scale images. In this method, a new histogram is generated according to the differences between pixels and their neighbouring pixels values. The proposed scheme can achieve higher embedding capacity than other existing reversible data hiding algorithms in the literature by considering the same value of peak signal‐to‐noise ratio. Experimental and analytical results show that this scheme is successfully employed for data hiding in a wide range of images.
Single image super‐resolution based on sparse representation using dictionaries trained with input image patches
Authors: Asgarian Dehkordi Rasoul , Khosravi Hossein , Ahmadyfard Alireza
Published: March 2020

In this study, an efficient self‐learning method for image super‐resolution (SR) is presented. In the proposed algorithm, the input image is divided into equal size patches. Using these patches, a dictionary is learned based on K‐SVD, referred to as high resolution (HR) dictionary. Then, by down‐sampling, the columns of the dictionary, called atoms, a low resolution (LR) version of the dictionary is obtained. An initial estimate of the SR image is constructed using the bicubic interpolation on the input image. Then in an iterative algorithm, the difference between the down‐sampled version of the estimated SR image and the input image is obtained. This difference image, which includes reconstructed details is enlarged using sparse representation and LR/HR dictionaries. The enlarged detail is added to the latest reconstructed SR image. This process gradually improves the quality of the initial SR image. After several iterations, the reconstructed image is an SR version of the input image. Experimental results confirm that the proposed method performance is promising.
Effect of vehicle composition on saturation flow at signalised intersections in mixed traffic conditions
Authors: Sushmitha Ramireddy , Ravishankar KVR
Published: March 2020

Vehicular traffic in most of the developing countries is a mixed traffic flow condition with non‐lane‐based behaviour in urban roads. Vehicles with different static and dynamic characteristics share a common lane. Signalised intersections provide sequential movements of vehicular traffic from one leg to another leg. Saturation flow is an important parameter for the measurement of the level of service at signalised intersections. The various equations, developed for the estimation of saturation flow, for a mixed traffic flow condition do not consider the non‐lane‐based traffic conditions. There is a need to establish a model to estimate the saturation flow of a signalised intersection for a non‐lane‐based vehicular movement in mixed traffic flow conditions. This research work presents the findings of the analysis of saturation flow conducted at signalised intersections in three different cities, Warangal, Raipur, and Calicut, in India. Flow rate and traffic volume data are collected using a video graphic technique and the Transportation Research Record Laboratory direct vehicle count method is used to estimate saturation flow. The developed model shows good predictability in comparison with observed data and can be used to estimate saturation flow in non‐lane‐based traffic conditions.
Driver emotion recognition of multiple‐ECG feature fusion based on BP network and D–S evidence
Authors: Wang Xiaoyuan , Guo Yongqing , Ban Jeff , Xu Qing , Bai Chenglin , Liu Shanliang
Published: March 2020

Driving emotion is considered as driver's psychological reaction to a change in traffic environment, which affects driver's cognitive, judgement and behaviour. In anxiety, drivers are more likely to get engaged in distracted driving, increasing the likelihood of vehicle crash. Therefore, it is essential to identify driver's anxiety during driving, to provide a basis for driving safety. This study used multiple‐electrocardiogram (ECG) feature fusion to recognise driver's emotion, based on back‐propagation network and Dempster–Shafer evidence method. The three features of ECG signals, the time–frequency domain, waveform and non‐linear characteristics were selected as the parameters for emotion recognition. An emotion recognition model was proposed to identify drivers’ calm and anxiety during driving. The results show after ECG evidence fusion, the proposed model can recognise drivers’ emotion, with an accuracy rate of 91.34% for calm and 92.89% for anxiety. The authors’ findings of this study can be used to develop the personalised driving warning system and intelligent human–machine interaction in vehicles. This study would be of great theoretical significance and application value for improving road traffic safety.
Investigation of transient energy storage sources for support of future electrical power systems
Authors: Hu Yiheng , Schofield Nigel , Shobayo Laolu Obafemi , Zhao Nan
Published: March 2020

The connection of renewable energy sources to local low‐voltage networks is becoming more accepted as electrical power networks progress to higher renewable penetration. Renewable energy resources, for example, wind and solar are highly dynamic and intermittent compared with more traditional generation sources, which imposes increasing challenges to the electrical network operator in terms of effectively managing the resource to maximise energy transfer and maintaining system stability. Therefore, transient energy storage systems (TESSs), for example, electrochemical batteries with fast charging/discharging capabilities are suitable candidates to improve the availability and reliability of connected renewable systems. In this study, two potential TESS technologies are presented, the lithium‐ion (Li‐ion) and sodium–nickel chloride (NaNiCl2) battery, and their feasibility to improve power systems in terms of power delivery and frequency fluctuations are compared. Experimentally validated battery models are presented and used to investigate the TESS performance in terms of state‐of‐charge, terminal voltage variation, peak current, power, energy and efficiency. The models and general design procedure may be applied to systems of different ratings and duty variations.
ADE-FDTD method for study of two-dimensional electromagnetic wave propagation in lossy lorentz medium
Authors: Chen Bingkang
Published: March 2020

In order to study the reflection of electromagnetic wave in Lorentz medium layer, the finite difference time domain method of auxiliary differential equation (ADE-FDTD) is used to derive the difference formula of two-dimensional TM wave propagating in lossy Lorentz medium, and the reflection coefficient of reflection field is calculated in one-dimensional case. The calculated reflection coefficients coincide very well, which shows that the derived propagation formula of two-dimensional TM wave in lossy Lorentz medium is correct. In addition, the reflection of plane electromagnetic wave by infinite high Lorentz medium layer is also simulated. The results show that the reflection of plane electromagnetic wave by Lorentz dispersive medium layer is correct.
Analysis of research on satellite network caching mechanism based on ICN
Authors: Liu Zhiguo , Li Yunqi
Published: March 2020

ICN was introduced into satellite networks to meet the growing demand for content acquisition. The caching mechanism is one of the most critical parts that profoundly affects the performance of the network. Based on the application background of satellite networks, the working mechanism of ICN and its technical advantages in introducing satellite networks are elaborated. The application status of ICN cache in satellite networks is analyzed to explore the applicability of existing caching mechanism in satellite networks, and the development and challenges of ICN caching mechanism in satellite network are analyzed.
A FPGA implementation of GMM MUD algorithm for space formation aircraft communication system
Authors: Ma Bo , Xu Mingdong , Wu Zhilu
Published: March 2020

Space formation aircraft communication system needs to meet strong anti-interference ability, low power consumption and high transmission rate performance. Ultra-wideband (UWB) has high data transfer rate, low device complexity, high interference resistance and confidentiality. Therefore, UWB technology is used in space formation aircraft communication system, which is direct sequence ultra-wideband (DS-UWB) space formation aircraft communication system. This paper, we put forward a multi-user detection (MUD) algorithm based on Gaussian Mixture Model (GMM) in DS-UWB communication system and its field-programmable gate array (FPGA) implementation. We adopt a way which based on MATLAB and FPGA platform, and results show that MUD algorithm based on GMM has better bit error rate (BER) performance compared to classical multi-user detection algorithm.
Research on situation awareness of network security assessment based on dempster-shafer
Authors: Zheng Weifa
Published: March 2020

There are a lot of uncertainties in the network security situation assessment that depends on is multi-source and heterogeneous. Therefore, the objective uncertainties must be described and dealt with in the process of network security situation assessment. This paper proposes a multi-attribute decision-making trust evaluation model based on D-S evidence theory in multi-source and heterogeneous environment. By collecting, processing and evaluating attack event information from many data sources of security device, it can effectively evaluate the possibility of network intrusion, and provide a new exploration for network security situation assessment.
Research on coverage control algorithm based on wireless sensor network
Authors: Zhou Jie , Xu Mengying , Lu Yi , Yang Rui
Published: March 2020

Wireless sensor network has many sensor nodes with characteristics of limited cost, collecting data, good fault tolerance and storage. It has been used in environmental monitoring, health care, military and commercial. Coverage control is a significant issue that needs to be solved in wireless sensor networks. In order to solve the problem of overlapping coverage for environmental monitoring and improve coverage rate, an improved immune fuzzy genetic algorithm (IIFGA) based on cluster head selection is proposed. the mathematical model is systematically described. In the experiments, ant colony optimization (ACO) and simulated annealing (SA) are given to compare the performance of IIFGA. The experiments show the proposed coverage control algorithm has a higher convergence speed and improve the coverage rate.
A music recommendation algorithm based on clustering and latent factor model
Authors: Jin Yingjie , Han Chunyan
Published: March 2020

The collaborative filtering recommendation algorithm is a technique for predicting items that a user may be interested in based on user history preferences. In the recommendation process of music data, it is often difficult to score music and the display score data for music is less, resulting in data sparseness. Meanwhile, implicit feedback data is more widely distributed than display score data, and relatively easy to collect, but implicit feedback data training efficiency is relatively low, usually lacking negative feedback. In order to effectively solve the above problems, we propose a music recommendation algorithm combining clustering and latent factor models. First, the user-music play record data is processed to generate a user-music matrix. The data is then analyzed using a latent factor probability model on the resulting matrix to obtain a user preference matrix U and a musical feature matrix V. On this basis, we use two K- means algorithms to perform user clustering and music clustering on two matrices. Finally, for the user preference matrix and the commodity feature matrix that complete the clustering, a user-based collaborative filtering algorithm is used for prediction. The experimental results show that the algorithm can reduce the running cost of large-scale data and improve the recommendation effect.
Research on the application of virtual instrument technology in simulation training
Authors: Xiao Qiang , Wang Long , Fang Juan , Xiao Guiping
Published: March 2020

This paper analyzes the feasibility of the application of GL Studio3.2 and Vega Prime2.2 software in combination, explores the application mode in the simulation system, and gives the call method of GL Studio3.2 control. Proposed by passing a pointer address way to deliver complex data types, with the method of window messaging to avoid the waste of time slices, with the method of thread messaging without window messaging method of thread.
Time series classification based on arima and adaboost
Authors: Wang Jinghui , Tang Shugang
Published: March 2020

In this paper, a novel time series classification approach, which using auto regressive integrated moving average model (ARIMA) features and Adaptive Boosting (AdaBoost) classifications. ARIMA is particularly suitable for distinguishing time series signal and Adaboost is suitable for features classification. The simulation results have shown that the algorithm is feasible. And this method is more accurate than many existing method in multiple time series problems.
A non-invasive blood viscosity detecting method based on pulse wave
Authors: Cui Fei , Chen Xiaohui , Peng Jie
Published: March 2020

A non-invasive blood viscosity detection method based on pulse wave is proposed. The method establishes a relationship equation between blood viscosity and peripheral resistance, arterial compliance, and pulse wave waveform characteristics by extracting characteristic parameters of human pulse wave. According to the blood viscosity model established by linear regression analysis, the human blood viscosity value is estimated to achieve non-invasive blood viscosity detection. The experimental results show that the blood using this method. The viscosity is in good agreement with the blood viscosity values measured by the blood viscometer.
Design of control system for driverless tractor
Authors: Li Yibo , Cao Qi , Liu Fang
Published: March 2020

This paper uses Tianjin TieNiu crawler tractor as the experimental platform to design an unmanned agricultural machinery control system based on RTK-GPS (Differential GPS Technology). The article expounds the overall design of the control system and proposes a path tracking control algorithm. Simulation and experimental results show that the control algorithm can complete the path tracking requirements of unmanned agricultural machinery. The system can control the unmanned agricultural machinery to follow a predetermined route. The speed is 0.55m/s, the maximum error of linear path tracking of agricultural machinery is 4.09cm, the average error is 2.20cm, the maximum error of large diameter circular path tracking is 20.67cm, the average error is 8.34cm, and the maximum error of continuous small diameter turning path tracking is 23.14cm, the average error is 7.38cm, both meet the operational requirements.
Research on manipulator grasping method based on vision
Authors: Yang Lei , Wu Shiliang , Lv Zhenlong , Lu Feng
Published: March 2020

Aiming at the problem that the manipulator cannot grasp the object accurately when the robot changes the position and pose of the object in the process of static grasping, a set of manipulator grasping method research based on vision is proposed. Firstly, a set of camera detection and robot grasping system model is built. Secondly, each coordinate system is created for the grasping system, and the transformation relation between each coordinate system, matrix model and the quantity that needs to be calibrated are introduced in detail. Thirdly, the trajectory function from the image coordinate system to the coordinates of the manipulator is obtained through the direct linear method calibration experiment. Finally, the experimental platform for camera detection and manipulator grasping objects based on xavis was built, and the grasping success rate of the experimental platform was tested. The experimental results show that the grasping error rate of the experimental platform is within the control range. Therefore, the manipulator grasping method based on vision is of reference significance for engineering applications.