bluuebunny/crossref_metadata_2025 huggingface dataset:
The intestinal microbiota contributes to the growth and physiological state of muscle tissue in piglets
Authors: Qi Renli , Sun Jing , Qiu Xiaoyu , Zhang Yong , Wang Jing , Wang Qi , Huang Jinxiu , Ge Liangpeng , Liu Zuohua
Published: May 2021

Although the importance of the intestinal microbiota in host growth and health is well known, the relationship between microbiota colonization and muscle development is unclear. In this study, the direct causal effects of the colonization of gut microorganisms on the muscle tissue of piglets were investigated. The body weight and lean mass of germ-free (GF) piglets were approximately 40% lower than those of normal piglets. The deletion of the intestinal microbiota led to weakened muscle function and a reduction in myogenic regulatory proteins, such as MyoG and MyoD, in GF piglets. In addition, the blinded IGF1/AKT/mTOR pathway in GF piglets caused muscle atrophy and autophagy, which were characterized by the high expression of Murf-1 and KLF15. Gut microbiota introduced to GF piglets via fecal microbiota transplantation not only colonized the gut but also partially restored muscle growth and development. Furthermore, the proportion of slow-twitch muscle fibers was lower in the muscle of GF piglets, which was caused by the reduced short-chain fatty acid content in the circulation and impaired mitochondrial function in muscle. Collectively, these findings suggest that the growth, development and function of skeletal muscle in animals are mediated by the intestinal microbiota.
Author Correction: Surface acoustic wave nebulization improves compound selectivity of low-temperature plasma ionization for mass spectrometry
Authors: Kiontke Andreas , Roudini Mehrzad , Billig Susan , Fakhfouri Armaghan , Winkler Andreas , Birkemeyer Claudia
Published: May 2021

An amendment to this paper has been published and can be accessed via a link at the top of the paper.
Retraction Note: The effect of soil nutrients and moisture during ontogeny on apparent wood density of Eucalyptus grandis
Authors: Castro Vinicius Resende , Chambi-Legoas Roger , Filho Mario Tommasiello , Surdi Paula Gabriella , Zanuncio José Cola , Zanuncio Antonio José Vinha
Published: May 2021

Editor's Note: this Article has been retracted; the Retraction Note is available at https://doi.org/10.1038/s41598-021-91048-y.
Comment on “Degradation of PFOS by a MnO2/H2O2 process” by Y. Chang, Y.-C. Cho and Y.-P. Lin, Environ. Sci.: Water Res. Technol., 2020, 6, 3476
Authors: Pham Anh Le-Tuan , Bruton Thomas A.
Published: May 2021

In this commentary, we express our reservation about the mechanism of PFOS degradation proposed by Chang et al. (Environmental Science Water Research & Technology, 2020, 6, 3476).
A novel MnO–CrN nanocomposite based non-enzymatic hydrogen peroxide sensor
Authors: Tareen Ayesha Khan , Khan Karim , Ahmad Waqas , Khan Muhammad Farooq , Khan Qudrat Ullah , Liu Xinke
Published: May 2021

A MnO–CrN composite was obtainedviathe ammonolysis of the low-cost nitride precursors Cr(NO3)3·9H2O and Mn(NO3)2·4H2O at 800 °C for 8 h using a sol–gel method.
Interface enriched highly interlaced layered MoS2/NiS2 nanocomposites for the photocatalytic degradation of rhodamine B dye
Authors: Harish S. , Bharathi P. , Prasad Prachi , Ramesh R. , Ponnusamy S. , Shimomura M. , Archana J. , Navaneethan M.
Published: May 2021

The photocatalytic performance of MoS2/NiS2 nanocomposites was studied by the degradation of rhodamine B (RhB). Ni-4 sample shows higher photocatalytic activity with a maximum degradation of 90.61% under visible light irradiation for 32 min.
A coupling process of electrodialysis with oxime hydrolysis reaction for preparation of hydroxylamine sulfate
Authors: Guan Fenggang , Chen Yanyan , Zhang Yuying , Yu Rujun
Published: May 2021

A coupling process of electrodialysis with oxime hydrolysis reaction for preparing hydroxylamine sulfate was developed in this work.
Aromatic side-chain flips orchestrate the conformational sampling of functional loops in human histone deacetylase 8
Authors: Shukla Vaibhav Kumar , Siemons Lucas , Gervasio Francesco L. , Hansen D. Flemming
Published: May 2021

Mechanistic description of how the active site of a hydrolase is connected with the functional loops at the periphery.
Proton-coupled electron transfer reactivities of electronically divergent heme superoxide intermediates: a kinetic, thermodynamic, and theoretical study
Authors: Mondal Pritam , Ishigami Izumi , Gérard Emilie F. , Lim Chaeeun , Yeh Syun-Ru , de Visser Sam P. , Wijeratne Gayan B.
Published: May 2021

Electronic characteristics of heme significantly influence the feasibility of hydrogen atom abstraction by synthetic heme superoxide moieties, shedding new light on analogous scenarios implicated in both biological and alternate energy applications.
Supporting nickel on vanadium nitride for comparable hydrogen evolution performance to platinum in alkaline solution
Authors: Shen Hangjia , Liang Shuqin , Adimi Samira , Guo Xuyun , Zhu Ye , Guo Haichuan , Thomas Tiju , Attfield J. Paul , Yang Minghui
Published: May 2021

The metal–support interaction between Ni and VN contributes to an outstanding performance for Ni/VN towards hydrogen evolution electrocatalysis following the Volmer–Tafel mechanism.
Pin‐loaded planar wideband end‐fire circularly polarised antenna
Authors: Yang Dongmei , Li Hongjun , Ren Baoquan , Cao Wenquan , Huang Ronggang
Published: May 2021

A single‐layer planar end‐fire circularly polarised microstrip antenna with enhanced bandwidth is proposed by loading with a metal pin. The original antenna is designed with a shorted parallel‐plate cavity that serves as a magnetic dipole, and a double‐sided printed bowtie dipole acts as an electric dipole. Then a metal pin is loaded connecting two metal surfaces and impedance bandwidth is improved obviously. One prototype is fabricated for verification and measured 19% –10 dB impedance bandwidth and 36% 3 dB axial ratio bandwidth are achieved.
The impact of lightning strike to multi‐blade on the lightning overvoltage and stresses of arresters in offshore wind farm
Authors: Zhang Jie , Han Yongxia , Li Licheng , Feng Shuaisong , Liao Zhiming
Published: May 2021

This paper establishes a complete lightning overvoltage simulation of an offshore wind farm, considering the electromagnetic effects including the blade, the tower and the power cable based on transmission‐line theory. And the influences of grounding schemes of the power cable inside the tower, different WTs struck by lightning, lightning current amplitude and the number of blades struck by lightning on lightning overvoltages of WT are all analysed. The results demonstrate that the grounding of both ends can effectively suppress the lightning overvoltages of WT. Second, the lightning overvoltages of WTs are related to their connection modes in case of lightning strike to different WTs, because of the differences of the equivalent impedance at the outlet of the WTs. Furthermore, the lightning overvoltages of WTs caused by lightning strike to double blades are larger than that caused by lightning strike to a single blade. In the case of the lightning current with an amplitude of 200 kA striking double blades, arresters should adopt multiple parallels connection to ensure the equipment would not be damaged. The distance between the tower and the power cable should be maintained approximately 0.25 m, to prevent the damage to power cable caused by flashover.
A receding horizon data‐driven chance‐constrained approach for energy flexibility trading in multi‐microgrid distribution network
Authors: Bagheri Zahra , Doostizadeh Meysam , Aminifar Farrokh
Published: May 2021

Unexpected imbalances between supply and demand during real‐time operation in the wake of high penetration of renewable energy resources necessitate system operators to improve flexibility of the system. Moreover, increasing growth in flexible distributed resources installation in distribution networks with multiple MicroGrids (MGs) such as fuel‐based distributed generators, storage units, and controllable loads makes distribution system operators be able to manage energy imbalances locally through exploiting potentials of aforementioned resources in flexibility enhancement. This paper proposes a receding horizon data‐driven chance‐constrained energy flexibility trading framework for active distribution networks with multiple MGs. Specifically, a distance‐based confidence set is constructed in a data‐driven manner to apply net load uncertainty into this modelling. According to this proposed data‐driven approach, the energy flexibility is modelled using flexibility envelope notion to demonstrate its dynamics in different scenarios in an imminent horizon. Furthermore, MGs' flexibility trading problem is modelled as an exact potential game that possesses a pure strategy Nash Equilibrium (NE). An iterative decentralized algorithm based on alternating direction method of multipliers is developed to achieve the NE strategy of MGs. Numerical results are also represented to show the performance efficiency of the proposed energy flexibility trading framework.
Micro‐Doppler frequency estimation and association via the inverse‐free complex SBL TVAR method
Authors: Su Nan , Dai Fengzhou , Liu Hongwei , Zhang Bo
Published: May 2021

A micro‐Doppler frequency estimation and association algorithm of the space target based on the time‐varying autoregressive (TVAR) model is proposed herein. The calculation time of the existing algorithms grows significantly with the problem size, and micro‐Doppler frequencies of different scattering centres are associated incorrectly where the frequencies intersect. The echo of the space target is modelled by the TVAR model, then the TVAR coefficients and instantaneous frequencies are estimated through the fast sparse Bayes learning (SBL) algorithm, finally, the micro‐Doppler frequencies of different scattering centres are associated in the frequency–frequency change rate domain. The effectiveness and rapidity of the proposed algorithm is demonstrated by simulation results.
A lighter core for Phobos?
Authors: Guo Xi , Yan Jianguo , Andert Tom , Yang Xuan , Pätzold Martin , Hahn Matthias , Ye Mao , Liu Shanhong , Li Fei , Barriot Jean-Pierre
Published: May 2021

Context.The origin of the Martian moons Phobos and Deimos is still poorly understood, and is the focus of intense debate.

Aims.We demonstrate that a stratified internal structure of Phobos is compatible with the observed gravity coefficients.

Methods.We fit previously derivedC20andC22Phobos gravity coefficients derived from the combined MEX Doppler-tracking data from the close flybys in +2010 and 2013 with respect to the corresponding coefficients of a core–mantle stratification model of Phobos, with two opposite cases: a core denser than the mantle, and a core lighter than the mantle.

Results.Only the case with a core lighter than the mantle fits at the 3σlevel the previously reported observed second degree and order coefficientC20, but a homogeneous Phobos cannot be strictly ruled out at the 3σlevel.

Conclusions.This possible loosening of the core density might be the result of a displacement of material toward the surface, may be caused by centrifugal forces acting on a loosely packed rubble-pile structure, and/or by a hot-then-cold in-orbit accretion process. These two hypotheses are by no means exhaustive.
State-constrained controllability of linear reaction-diffusion systems
Authors: Lissy Pierre , Moreau Clément
Published: May 2021

We study the controllability of a coupled system of linear parabolic equations, with nonnegativity constraint on the state. We establish two results of controllability to trajectories in large time: one for diagonal diffusion matrices with an “approximate” nonnegativity constraint, and a another stronger one, with “exact” nonnegativity constraint, when all the diffusion coefficients are equal and the eigenvalues of the coupling matrix have nonnegative real part. The proofs are based on a “staircase” method. Finally, we show that state-constrained controllability admits a positive minimal time, even with weaker unilateral constraint on the state.
On numerical approximation of Atangana-Baleanu-Caputo fractional integro-differential equations under uncertainty in Hilbert Space
Authors: Al-Smadi Mohammed , Dutta Hemen , Hasan Shatha , Momani Shaher
Published: May 2021

Many dynamic systems can be modeled by fractional differential equations in which some external parameters occur under uncertainty. Although these parameters increase the complexity, they present more acceptable solutions. With the aid of Atangana-Baleanu-Caputo (ABC) fractional differential operator, an advanced numerical-analysis approach is considered and applied in this work to deal with different classes of fuzzy integrodifferential equations of fractional order fitted with uncertain constraints conditions. The fractional derivative of ABC is adopted under the generalized H-differentiability (g-HD) framework, which uses the Mittag-Leffler function as a nonlocal kernel to better describe the timescale of the fuzzy models. Towards this end, applications of reproducing kernel algorithm are extended to solve classes of linear and nonlinear fuzzy fractional ABC Volterra-Fredholm integrodifferential equations. Based on the characterization theorem, preconditions are established under the Lipschitz condition to characterize the fuzzy solution in a coupled equivalent system of crisp ABC integrodifferential equations. Parametric solutions of the ABC interval are provided in terms of rapidly convergent series in Sobolev spaces. Several examples of fuzzy ABC Volterra-Fredholm models are implemented in light of g-HD to demonstrate the feasibility and efficiency of the designed algorithm. Numerical and graphical representations of both classical Caputo and ABC fractional derivatives are presented to show the effect of the ABC derivative on the parametric solutions of the posed models. The achieved results reveal that the proposed method is systematic and suitable for dealing with the fuzzy fractional problems arising in physics, technology, and engineering in terms of the ABC fractional derivative.
Assessment of quality benchmarks in adenoma detection in Mexico
Authors: Aguilar-Olivos Nancy E. , Balanzá Ricardo , Rojas-Mendoza Fernando , Soto-Solis Rodrigo , Ballesteros-Amozurrutia Mario A. , González-Uribe Norma , Fernández-Rivero Justo A.
Published: May 2021

Background and study aims Several Latin American countries, including Mexico, have reported an increase in colorectal cancer (CRC) mortality. The effectiveness of a colonoscopy in preventing CRC depends on the quality of the procedure, for which the adenoma detection rate (ADR) is one of the most trusted indicators. Awareness of ADR can improve the quality of colonoscopies through proper feedback and training of the specialists. The goal of this study was to estimate the ADR among Mexican endoscopists with experience in CRC screening and to compare it with previously reported data from this country.

Methods We carried out a retrospective study to analyze ADR data in Mexico. The information was obtained from a group of certified endoscopists and compared with the former published data from Mexico.

Results We found a current ADR of 24.6 % (95 %CI, 22.4 %–26.8 %) from 1,478 colonoscopies performed by eight endoscopists in two third-level private hospitals. The average ADR reported in previous publications was 15.2 % (95 %CI, 13.3 %–17.1 %). Statistical analysis showed differences between our results and those from previous studies (24.6 % vs. 15.2 %, P < 0.001).

Conclusions The actual ADR in Mexico is higher than previously reported. Previous low ADR values could be explained by poorly performed colonoscopies rather than by low adenoma and CRC incidence in our country.
Development of a gel dedicated to gel immersion endoscopy
Authors: Yano Tomonori , Ohata Atsushi , Hiraki Yuji , Tanaka Makoto , Shinozaki Satoshi , Lefor Alan Kawarai , Yamamoto Hironori
Published: May 2021

Backgrounds and study aims Gel immersion endoscopy is a novel technique to secure the visual field during endoscopy. The aim of this study was to develop a dedicated gel for this technique.

Methods To identify appropriate viscoelasticity and electrical conductivity, various gels were examined. Based on these results, the dedicated gel “OPF-203” was developed. Efficacy and safety of OPF-203 were evaluated in a porcine model.

Results 
In vitro experiments showed that a viscosity of 230 to 1900 mPa·s, loss tangent (tanδ) ≤ 0.6, and hardness of 240 to 540 N/cm2 were suitable. Ex vivo experiments showed electrical conductivity ≤ 220 μS/cm is appropriate. In vivo experiments using gastrointestinal bleeding showed that OPF-203 provided clear visualization compared to water. After electrocoagulation of gastric mucosa in OPF-203, severe coagulative necrosis was not observed in the muscularis but limited to the mucosa.

Conclusions OPF-203 is useful for gel immersion endoscopy.
Do endosonographers agree on the presence of bile duct sludge and the subsequent need for intervention?
Authors: Quispel Rutger , Schutz Hannah M. , Hallensleben Nora D. , Bhalla Abha , Timmer Robin , van Hooft Jeanin E. , Venneman Niels G. , Erler Nicole S. , Veldt Bart J. , van Driel Lydi M.J.W. , Bruno Marco J.
Published: May 2021

Background and study aims Endoscopic ultrasonography (EUS) is a tool widely used to diagnose bile duct lithiasis. In approximately one out of five patients with positive findings at EUS, sludge is detected in the bile duct instead of stones. The objective of this study was to establish the agreement among endosonographers regarding: 1. presence of common bile duct (CBD) stones, microlithiasis and sludge; and 2. the need for subsequent treatment.

Patients and methods 30 EUS videos of patients with an intermediate probability of CBD stones were evaluated by 41 endosonographers. Experience in EUS and endoscopic retrograde cholangiopancreatography, and the endosonographers’ type of practices were recorded. Fleiss’ kappa statistics were used to quantify the agreement. Associations between levels of experience and both EUS ratings and treatment decisions were investigated using mixed effects models.

Results A total of 1230 ratings and treatment decisions were evaluated. The overall agreement on EUS findings was fair (Fleiss’ κ 0.32). The agreement on presence of stones was moderate (κ 0.46). For microlithiasis it was fair (κ 0.25) and for sludge it was slight (κ 0.16). In cases with CBD stones there was an almost perfect agreement for the decision to subsequently perform an ERC + ES. In case of presumed microlithiasis or sludge an ERC was opted for in 78 % and 51 % of cases, respectively. Differences in experience and types of practice appear unrelated to the agreement on both EUS findings and the decision for subsequent treatment.

Conclusions There is only slight agreement among endosonographers regarding the presence of bile duct sludge. Regarding the need for subsequent treatment of bile duct sludge there is no consensus.
Resistance against Erosive Challenge of Dental Enamel Treated with 1,450-PPM Fluoride Toothpastes Containing Different Biomimetic Compounds
Authors: Fernandes Nayanna L. S. , Juliellen L. da Cunha , Andressa F. B. de Oliveira , D’Alpino H. P. Paulo , Sampaio C. Fábio
Published: May 2021

Objectives This in vitro study aimed to characterize the superficial and subsurface morphology of dental enamel treated with fluoridated gels containing different biomimetic compounds after erosive challenge.

Materials and Methods Bovine incisor teeth were sectioned to obtain enamel blocks (4 mm × 4 mm × 6 mm; n = 5) that were demineralized to create an artificial caries lesion and treated by pH cycling interspersed with exposure to fluoridated toothpaste slurries under agitation. During pH cycling (demineralization and remineralization for 2 and 22 hours, respectively) for 6 days, the enamel blocks were exposed to toothpaste slurries under agitation with one of the dental gels: Regenerate Enamel Science (NR-5 technology), Daily Regenerator Dental Clean (REFIX technology), and Sensodyne Repair & Protect (Novamin technology). The enamel blocks were subjected to an erosive challenge, immersed in 50% citric acid for 2 minutes, and then washed with plenty of distilled water. The surface and cross-sectional micromorphology were assessed using scanning electron microscope (SEM). The elemental analyses (weight percentage) were determined with an energy-dispersive X-ray spectroscopy (EDS).

Results Enamel treated with the product containing REFIX technology presented a smoother surface morphology compared to the other treatments. The higher resistance to the erosive challenge can be attributed to a silicon-enriched mineral layer formed on the enamel induced by the REFIX-based toothpaste. This was not observed in the specimens treated with the other technology-containing toothpastes.

Conclusion The REFIX technology seemed to be the most promising compared to the Novamin and NR-5 technologies. In addition to forming a surface mineralized layer, the enamel treated with REFIX technology associated with the pH cycling resisted a subsequent erosive challenge.
Does Accountability Undermine Service Delivery? The Impact of Devolving Agriculture in Ghana
Authors: Resnick Danielle
Published: May 2021

In recent years, many developing countries have devolved services to locally elected governments. Although this may strengthen downwards accountability to citizens, does devolution improve service provision? Ghana began devolving agriculture in 2012 to its Metropolitan, Municipal, and District Assemblies (MMDAs). Drawing on an original survey with 80 District Directors of Agriculture and 960 households, as well as district-level budget data and interviews with national and local government stakeholders, this paper shows that agricultural expenditures and services have been negatively affected by the transition. The imperative of electoral accountability encourages assembly members to de-prioritize agriculture in the budget process in favor of more visible goods and services. Budget allocations, however, do reflect the preferences of local citizens, a majority of whom value using elections to sanction their district politicians. The findings indicate that devolution may increase accountability but result in sectoral trade-offs in service provision, which may undermine national policy objectives.
Pressure sensor enables normal stress measurements in non-Newtonian fluids
Authors: Johnson-Groh Mara
Published: May 2021

A piezo-capacitive pressure sensor allows stress characterization of non-Newtonian fluids for the first time.
Seed nanopriming by silicon oxide improves drought stress alleviation potential in wheat plants
Authors: Rai-Kalal Prabha , Tomar Rupal S. , Jajoo Anjana
Published: May 2021

The present study explored the effectiveness of SiO2 nanoparticles (NPs) as seed priming agent (15 mg L–1) to improve drought tolerance in the wheat cultivar HI 1544. Seed germination studies showed significant enhancement in the rate of seed germination, seedling growth and vigour, seed water uptake, and amylase activity in nanoprimed (NP) seeds compared with unprimed (UP) seeds. Pot experiments using wheat plants subjected to drought stress showed that SiO2 nanopriming enhanced the ability of wheat plants to withstand water deficit conditions by balancing the production of reactive oxygen species and the activity of enzymatic antioxidants like peroxidase, catalase, and superoxide dismutase. Investigations of photosynthetic parameters showed that under drought conditions, nanoprimed plants had a higher number of active reaction centres, high absorbance, trapping, and electron transport rates compared with unprimed plants. These results suggest the effects of silicon nanopriming in enhancing drought tolerance in wheat by alleviating drought induced inhibition of plant photosynthetic machinery and maintaining biochemical balance, ultimately resulting in an increase in biomass production. Results revealed the use of silicon oxide nanopriming to be a good option to increase drought tolerance in wheat plants.
Effect of long-term crop rotation and fertilisation management on soil humus dynamics in organic and sustainable agricultural management systems
Authors: Masilionytė Laura , Kriaučiūnienė Zita , Šarauskis Egidijus , Arlauskienė Aušra , Krikštolaitis Ričardas , Šlepetienė Alvyra , Jablonskytė-Raščė Danutė , de Jong van Lier Quirijn
Published: May 2021

The integration of organic fertilisers into agricultural practices is one approach to enable more efficient agricultural management systems to decrease adverse environmental impacts of agriculture. In this context, the objective of this research was to determine the impact of long-term crop rotation and organic and mineral fertilisation on soil humus content, humic and fulvic acids, organic matter humification in organic and sustainable agricultural management systems with low (1.90–2.01%) and moderate (2.10–2.40%) initial humus contents. Long-term field experiments with different agricultural management systems started in 1960 at the Lithuanian Research Centre for Agriculture and Forestry and soil humus dynamics experiments were conducted from 2006 to 2017. Results of the long-term use of organic and sustainable agricultural management systems with different crop rotations and fertilisation revealed the positive effect of the applied supplies on soil humus, especially for farmyard manure in combination with green manure. The incorporation of farmyard manure and biomass of white mustard resulted in a lower degree of humification when compared to green manure alone, green manure + mineral N, and farmyard and green manure + mineral N. In the low humus content soil, the degree of humification under all agricultural management systems was significantly improved, on average by 0.9% compared to soil with a moderate humus content.
Vincetoxicum nigrum (black swallowwort).
Authors: Gassmann André
Published: May 2021

V. nigrum is a herbaceous climbing vine native to south-western Europe (Italy, France, Portugal and Spain). It has spread extensively throughout New England, the lower Hudson River basin and south-eastern Pennsylvania, USA. V. nigrum produces a large number of wind-borne, self-fertile seeds which readily disperse to new sites. Small patches of V. nigrum can coalesce to form large, monospecific stands that outcompete with native vegetation and alter habitats. In Vermont and New Hampshire, USA, the endemic and endangered species, Astragalus robbinsii var. jesupii, is under pressure by an expanding population of V. nigrum. In addition to this V. nigrum may have negative impact on the monarch butterfly, Danaus plexippus.
Large-area fabrication: The next target of perovskite light-emitting diodes*
Authors: Su Hang , Zhu Kun , Qin Jing , Li Mengyao , Zuo Yulin , Wang Yunzheng , Wu Yinggang , Cao Jiawei , Li Guolong
Published: May 2021

Perovskite materials show exciting potential for light-emitting diodes (LEDs) owing to their intrinsically high photoluminescence efficiency and color purity. The research focusing on perovskite light-emitting diodes (PeLEDs) has experienced an exponential growth in the past six years. The maximum external quantum efficiency of red, green, and blue PeLEDs has surpassed 20%, 20%, and 10%, respectively. Nevertheless, the current PeLEDs are still in the laboratory stage, and the key for further development of PeLEDs is large-area fabrication. In this paper, we briefly discuss the similarities and differences between manufacturing high-quality and large-area PeLEDs and perovskite solar cells. Especially, the general technologies for fabricating large-area perovskite films are also introduced. The effect of charge transport layers and electrodes on large-area devices are discussed as well. Most importantly, we summarize the advances of large-area (active area ≥ 30 mm2) PeLEDs reported since 2017, and describe the methods for optimizing large-area PeLEDs reported in the literature. Finally, the development perspective of PeLEDs is presented for the goal of highly efficient and large-area PeLED fabrication. It is of great significance for the application of PeLEDs in future display and lighting.
Degradation and its fast recovery in a-IGZO thin-film transistors under negative gate bias stress*
Authors: Guo Jianing , Zhang Dongli , Wang Mingxiang , Wang Huaisheng
Published: May 2021

A new type of degradation phenomena featured with increased subthreshold swing and threshold voltage after negative gate bias stress (NBS) is observed for amorphous InGaZnO (a-IGZO) thin-film transistors (TFTs), which can recover in a short time. After comparing with the degradation phenomena under negative bias illumination stress (NBIS), positive bias stress (PBS), and positive bias illumination stress (PBIS), degradation mechanisms under NBS is proposed to be the generation of singly charged oxygen vacancies (

V
o
+

) in addition to the commonly reported doubly charged oxygen vacancies (

V
o

2
+

). Furthermore, the NBS degradation phenomena can only be observed when the transfer curves after NBS are measured from the negative gate bias to the positive gate bias direction due to the fast recovery of

V
o
+

under positive gate bias. The proposed degradation mechanisms are verified by TCAD simulation.
Physical and mechanical properties of insulation from rubber leave
Authors: Anantanukulwong R
Published: May 2021

This research aims to study the insulation sheet of rubber leaves. By testing physical properties and mechanical property at the ratio of rubber leave : rubber latex were 20:80, 30:70, 40:60, 50:50, 60:40, 70:30 and 80:20. Use rubber latex as a binder to allow the material to be bonded. The insulating sheets produced are smooth 16×16×2 cm3. From the results showed that the moisture content of the sample were 6.722 - 14.747%. The tensile strength were 0.0002 – 0.0288 MPa. The fire spread rate were run of 0 - 6.640 mm/min and the ratio of 70:30 and 80:20 were no fire spread rate. Then finally, the heat conductivity coefficient were 0.0283 - 0.0442 W/m·K. Moreover, samples of ratio 80:20 have a better conductivity coefficient than commercial insulation and confirmed with the SEM-EDX analysis.
Development and Validation of QT Interval Measurement Algorithm Using Lab windows/CVI
Authors: Ramya B , Chaithanya D J , Aisiri A P , Anitha S
Published: May 2021

During the last few years, a lot of study and research on the analysis of Electrocardiogram(ECG) has provided an intensive approach for the diagnosis of various heart diseases which is a leading cause of death worldwide. By examining the ECG waveform it is possible to obtain a number of useful measurements. The most important of these is the “QT interval” measurement because an abnormal QT interval can be allied with ventricular arrhythmias and sudden cardiac death. The QT interval is obtained by the detection of onset of the QRS complex and offset of the T wave. This work includes an endeavor for the efficient measurement of QT interval which mainly comprises of five stages like finding R peak using Pan Tompkins algorithm, detection of QRS onset, detection of T wave offset, measurement of QT interval and QT interval correction. The measurement of QT interval is implemented using LabWindows/CVI (C for Virtual Instrumentation). The performance evaluation of R peak detection is tested as per AAMI/ANSI/IEC 60601-2-47 standards using the databases that are available in Physionet like QT Database and MIT-BIH Arrhythmia Database. The performance evaluation of QT interval measurement is tested using a MindrayuMEC 10 Multiparametric monitoring unit and the algorithm achieved an accuracy of 96.73% for QT interval measurement.
Computer Vision based Early Electrical Fire-detection in Video Surveillance oriented for Building environment
Authors: Sridhar P , Sathiya R R
Published: May 2021

This work presents autonomous electrical fire-detection and localization using computer vision based techniques. The proposed work uses YOLO v2 to extract the electrical fire features more effectively than other conventional and machine learning approaches. This working model is tested on commercial and residential building as well as indoor and outdoor environments. This framework has achieved high detection accuracy and low false alarm rate. Besides, the proposed frame work can be used for early real-time electrical fire detection in surveillance videos and we present experimental results for electrical fire localization in CCTV footage using the deep learning architecture proposed in this work.
Multiview 3D detection system for automotive driving
Authors: Suresh Kumar S , Sathish Kumar T , Saravana Kumar M , Subramanian G
Published: May 2021

For the past few years, there has been an increase in road accidents all over the world. The most common crucial reason is drowsiness. The presented work deals with this problem to reduce the number of accidents while keeping the methodologies simple and intact with the usage of computer vision applications like blink rate, eye closure, yawning. Detection of the driver’s drowsiness is done by a single-camera attached behind the steering wheel and to identify yawning and for alerting the driver, a buzzer is triggered when the eyes are closed and also when the count of yawning is greater than the specific rate. The system will also work even the driver is wearing glasses and it can be implemented with the comfort of a pocket phone.
Improved Cost Effective IoT Based Coal Mining Safety System
Authors: Jayarajan P , Gayathri K V , Gowshikha S , Harini N
Published: May 2021

In recent years there are lot of life risk occurs to skilled labors in coal mines which requires an advancement in coal mining safety system. In order to improve this current scenario, An IOT based coal mining safety system is proposed. Proposed system is implemented using IOT module to monitor and control various parameters in the coal mines such as leakage of gas, earthquake, water level and Fire ignition detection in the coal mine. All these sensors are intergrated with microcontroller and placed in different parts of coal mines. In case of any uncertainties then buzzer will alert, then the notification is sent to the serial monitor and to the authorized person. This system enhances the safety and improved working conditions of labours in coal mining system.
Truth discovery in healthcare prediction using machine learning
Authors: Priyanka G , Mahalakshmi M , Nivedha G , Roshini J
Published: May 2021

Healthcare is one of the core areas of the medical field in today’s digital world. By analyzing large amounts of patient data, healthcare systems are needed to gain insights and help disease prediction. The truth discovery of the Health Recommendation System (TDHRS) is becoming an important platform for medical services. The proposed use of Boltzmann Machine (RBM)-FP-Growth Health Pattern Recognition (RBMG) smart HRS can provide insights into how big data analysis can be used to implement an effective health recommendation engine, and will be used in Transition from a standard solution to a more personalized paradigm in the telemedicine environment. By considering the Root Mean Square Error (RSME) and Mean Absolute Error (MAE) values, the proposed deep learning method (RBM-FP-Growth) exhibits fewer errors than other methods.
Automatic Voting System Using Convolutional Neural Network
Authors: Sruthi M S , Shanjai K
Published: May 2021

Electoral fraud or election fraud is an illegal intervention in the process of election, in which voters vote repeatedly for a favored party thereby increasing vote share. In Order to conduct elections ethically, this election fraud should be eliminated. Hence, the automatic voting system using Convolutional Neural Network (CNN) has been proposed. The Existing systems are time-consuming and difficult-to-maintain since they include manual processes. Presently different kinds of biometric processes available, among that face detection is the most effective. The proposed system develops an automatic voting system without any human intervence. This system includes a camera for capturing the images of electors, captured images will be stored in the database for analysis. data analysis will be performed on the database. In this method, all the label images are trained through the convolutional neural network to predict the output by classifying the images. This classification system produces an accuracy of approximately 90%.
A Secure Remote Clinical Sensor Network Approach for Privacy Enhancement
Authors: Sophia B , Jeril L , Kavin Harnesh M , Lalith Kumar V
Published: May 2021

Health being the biggest concern of the patients all around the globe, e-healthcare Remote Clinical Sensor Network assists in gathering the crucial body information of individual boundaries using sensors. There are chances forlots of issues like absence of vigor, diminished framework’s adequacy, bogus caution, since it is remote in nature. The security and protection assurance of the information gathered has been a major concern factor to worry about. Hence, we presented fused secure and fuzzy combination framework focusing on these issues to accomplish productive secure transmission and information combination. The proposed technique is on thought of providing a secured key and encoded by AES i.e., Advanced Encryption Standard mechanism. It handles loose information for less utilization of energy and therefore increasing the lifetime of the network. And thus the experimental results ensure the energy utilization, security and the proficiency of the put forth strategy.
Securing Connected & Autonomous Vehicles: Challenges posed by Adversarial Machine Learning and the way forward
Authors: Kiruthika S , Aashin A , Gopinath K , Gowtham A
Published: May 2021

Associated and self-ruling automobiles (CAVs) will shape a foundation for the future cutting edge canny transport frameworks (ITS) giving comfortable travelling, street wellbeing, alongside various worth added administrations. Such a change—which would be fuelled by attendant advances on advances for AI (Machine Learning) and remote interchanges—will empower a future vehicular biological system that is better included and more effective. Notwithstanding and are sneaking security issues identified with the utilization of Machine Learning in a particularly basic setting where a mistaken Machine Learning choice may not exclusively be an aggravation yet can prompt loss of valuable lives. Here it’s present a top to bottom outline of the different difficulties related with the utilization of Machine Learning In vehicular organizations. Moreover, we form the Machine Learning Pipeline of CAVs and present different potential security issues related with the selection of Machine Learning Strategies. Specifically, it’s center around the point of view of antagonistic Machine Learning Assaults on CAVs and framework an answer for protecting against ill-disposed assaults in different settings.
Machine Learning based Fraud Analysis and Detection System
Authors: Kousika N , Vishali G , Sunandhana S , Vijay M Arvind
Published: May 2021

The spectacular surge in the proportion of credit card transactions, web based purchases, has led to a surge in fraudulent activities recently. For any business establishment, credit card security is a major concern. In this respect, credit card fraud is hard to identify. Thus it became imperative to implement effectual fraud detection systems for all credit card issuing banks to mitigate their losses. Betrayed transactions with real transactions in actuality are often dispersed and simple methods of matching are not enough to detect them accurately. The paper proposes an algorithm based on Machine Learning credit card fraud detection to solve the issue of a fraudulent transaction. This framework nominally increases the probability of card fraud by exponential activity. The results show that the accuracy of Random Forest, Support Vector Machine and KNN classifiers achieves respectively 94.84%, 89.46%. Random Forest could even predict new fraud cases very quickly.
Dual Axis Solar Tracking System using LDR Senors
Authors: Krishna Kumar J. , Nivas J. , Sankar S. , Uthirasamy R.
Published: May 2021

At present, the dual axis solar system is not being used properly. A single axis of solar energy system is more compact and more widely used than a double axis. However, a single axis tracking system is less effective but more efficient due to its economic viability. Therefore, we are analysing a double axis tracking system preferred tosingle axis tracking system. We use an independent method using a dummy solar tracker to check whether the sun’s rays reflected on the solar panel at a specific point at any given time based on the elevation calculations and azimuth angles of sunrays. To simulate the processes a simulation using the Borland C ++ builder is created. Here, azimuth-elevation angles are calculated accurately and precisely in any location and time.
Ultrasonic sensor enabled smart automated railway gate control system
Authors: Senthil Kumar R , Prabu M , Rani K S , Prabaakaran K , Chowdary Penekalapati Soniya , Rithika K
Published: May 2021

Railways is the most preferred modes of transport system for freights as well as passengers. Among the accidents occurring in railways, the accident due to unmanned railway crossing are predominant. This article focuses in providing a smart automatic solution for vigilant monitoring in avoiding the accidents in railway crossing, system is provided with extra features to perform superior to raw conventional automatic railway gate, instead of blind closing of gates, gates are provided with the sensor which detect any persons or vehicle beneath it when it is operated. Along gate, pop up projection are recommended in this system which will be effectively restricting the movement across railway crossing during the operation of gates. Additionally, a monitoring system is provided which gives signal to train drivers if any vehicle/living being got struck in between the railway gate, well in advance which aids train drivers to act accordingly. Along with all these additional features conventional alarm feature is also available to alert. The prototype designed with the above feature effectively gives a solution in avoiding accidents by strongly enforce the restriction in movement across the gates when train crossing the unmanned railway crossing, reaction time of the monitoring system in giving alert to train driver, if any vehicle/living being got locked between the gates is very low.
Deep Learning based Voice assistance in hospitals using Face Recognition
Authors: Jenifa G , Yuvaraj N , Karthikeyan B , Preethaa K R Sri
Published: May 2021

After listening to a wake word or order, voice assistants come in quite compact packages and can accomplish a range of acts. They are able to switch on the lights, answering basic questions, playing music, place online orders, etc. As voice assistants become more robust, their usefulness can also be extended in both the personal and business areas. Various descriptive variables are fused in speech signals, leading to considerable difficulties interpreting any of the variables. There are various effective algorithms for speech and face recognition for the real - world applications. When a human try to communicate with a bot or vice-versa, there occurs so many difficulties in information sharing. This paper deals with one such application of bot assistance in hospitals, where a patient communicates with the bot assistant. Though the task seems to be quite easy, it involves a main threat: surrounding noise, word error rate, accuracy of the speech. An obvious impression is to factorize the frame of audio into various enlightening variables, but it turns out to be extremely difficult. The face of the patient who enters the healthcare premise is captured and analysed through the Deep Neural Network (DNN) based face recognition algorithm. Once identifying the user, the information regarding the patient is gathered from the database and given as a voice over output. Now, it is necessary to measure the accuracy of the word recognition and the word error rate. For this Cascade Deep Factorization (CDF) and Iterative Signal Enhancement (ISE) algorithm are used and discussed in this paper. For several speech processing functions like speaker recognition, this factorization and reconstruction method offers possible values.
Full Fledged Automated Human Resource Management Software Suite
Authors: Sivasankaran M Sri , Suganya T
Published: May 2021

The Human Resource Management System is essentially worried about dealing with the Administrator of HUMAN RESOURCE Department in an organization. A Human Resource Management System alludes to the frameworks and cycles at the crossing point between human asset the executives and data innovation. It blends HRM as an order and specifically its essential HR exercises and cycles with the data innovation field, though the programming of information preparing frameworks developed into full-fledged HR SUITE. The fundamental target of this paper is to diminish the exertion of Administrator to keep the day-by-day occasions, for example, participation, projects, works, arrangements, and so forth This paper manages the way toward distinguishing the representatives, recording their participation hourly and ascertaining their successful payable hours or days. This paper FULL fledged HR management suite ought to keep up the records of every single worker and their time spend in to organization, which can be utilized for execution evaluation. In view of that move, expulsion, advancement should be possible.
Phishing website detection using machine learning and deep learning techniques
Authors: Selvakumari M , Sowjanya M , Das Sneha , Padmavathi S
Published: May 2021

Phishing has become more damaging nowadays because of the rapid growth of internet users. The phishing attack is now a big threat to people’s daily life and to the internet environment. In these attacks, the attacker impersonates a trusted entity intending to steal sensitive information or the digital identity of the user, e.g., account credentials, credit card numbers and other user details. A phishing website is a website which is similar in name and appearance to an official website otherwise known as a spoofed website which is created to fool an individual and steal their personal credentials. So, to identify the websites which are fraud, this paper will discuss the machine learning and deep learning algorithms and apply all these algorithms on our dataset and the best algorithm having the best precision and accuracy is selected for the phishing website detection. This work can provide more effective defenses for phishing attacks of the future.
Machine Learning based Classification for Heart Disease Identification
Authors: Siamala Devi S , Harini Karthika G , Deepika M
Published: May 2021

Cardiac illness is one of the unpredictable infections and around the world numerous individuals experienced this sickness. On schedule and effective recognizable proof of coronary illness assumes a critical part in medical care, especially in the arena of cardiology. A productive and precise framework is proposed to finding coronary illness and the framework depends on AI procedures. Supervised learning algorithms such as Multi-Layer Perceptron (MLP), Multinomial Logistic Regression (MLR), Fuzzy Unordered Rule Induction Algorithm (FURIA) and C4.5 are then used to model CAD cases. This approach is tested on medical data that has 26 features and 335. MLR accomplishes most noteworthy expectation precision of 88.4 %. This methodology is benchmarked on Cleveland heart coronary illness information also. For this situation additionally, MLR, beats different methods. Projected hybridized model increases the exactness of arrangement calculations from 8.3 % to 11.4 % for the Cleaveland information. The proposed technique is, along these lines, a promising tool for finding CAD patients with improved forecast precision.