bluuebunny/crossref_metadata_2025_split huggingface dataset:
Influence of dielectric layer thickness on charge injection, accumulation and transport phenomena in thin silicon oxynitride layers: a nanoscale study
Authors: Mortreuil F , Boudou L , Makasheva K , Teyssedre G , Villeneuve-Faure C 
Published: October 2020

Abstract
Charge injection and retention in thin dielectric layers remain critical issues due to the great number of failure mechanisms they inflict. Achieving a better understanding and control of charge injection, trapping and transport phenomena in thin dielectric films is of high priority aiming at increasing lifetime and improving reliability of dielectric parts in electronic and electrical devices. Thermal silica is an excellent dielectric but for many of the current technological developments more flexible processes are required for synthesizing high quality dielectric materials such as amorphous silicon oxynitride layers using plasma methods. In this article, the studied dielectric layers are plasma deposited SiO
x
N
y
. Independently on the layer thickness, they are structurally identical: optically transparent, having the same refractive index, equal to the one of thermal silica. Influence of the dielectric film thickness on charging phenomena in such layers is investigated at nanoscale using Kelvin probe force microscopy (KPFM) and conductive atomic force microscopy. The main effect of the dielectric film thickness variation concerns the charge flow in the layer during the charge injection step. According to the SiO
x
N
y
layer thickness two distinct trends of the measured surface potential and current are found, thus defining ultrathin (up to 15 nm thickness) and thin (15–150 nm thickness) layers. Nevertheless, analyses of KPFM surface potential measurements associated with results from finite element modeling of the structures show that the dielectric layer thickness has weak influence on the amount of injected charge and on the decay dynamics, meaning that pretty homogeneous layers can be processed. The charge penetration depth in such dielectric layers is evaluated to 10 nm regardless the dielectric thickness.
On stationary solutions and inviscid limits for generalized Constantin–Lax–Majda equation with O(1) forcing
Authors: Jeong In-Jee , Kim Sun-Chul 
Published: October 2020

Abstract
The generalized Constantin–Lax–Majda (gCLM) equation was introduced to model the competing effects of advection and vortex stretching in hydrodynamics. Recent investigations revealed possible connections with the two-dimensional turbulence. With this connection in mind, we consider the steady problem for the viscous gCLM equations on

T

:

a
v

ω

x

−

v

x

ω
=
ν
Δ
ω
+
f
,
v
=

(

−
Δ

)

−

1

2

ω
,

where

a
∈
R

is the parameter measuring the relative strength between advection and stretching, ν > 0 is the viscosity constant, and f is a given O(1)-forcing independent of ν. For some range of parameters, we establish existence and uniqueness of stationary solutions. We then numerically investigate the behaviour of solutions in the vanishing viscosity limit, where bifurcations appear, and new solutions emerge. When the parameter a is away from [−1/2, 1], we verify that there is convergence towards smooth stationary solutions for the corresponding inviscid equation. Moreover, we analyse the inviscid limit in the fractionally dissipative case, as well as the behaviour of singular limiting solutions.
Generating boundary conditions for a Boussinesq system*
Authors: Lannes D , Weynans L 
Published: October 2020

Abstract
We present a new method for the numerical implementation of generating boundary conditions for a one dimensional Boussinesq system. This method is based on a reformulation of the equations and a resolution of the dispersive boundary layer that is created at the boundary when the boundary conditions are non homogeneous. This method is implemented for a simple first order finite volume scheme and validated by several numerical simulations. Contrary to the other techniques that can be found in the literature, our approach does not cause any increase in computational time with respect to periodic boundary conditions.
Recording and quantifying fetal magnetocardiography signals using a flexible array of optically-pumped magnetometers
Authors: Escalona-Vargas Diana , Bolin Elijah H , Lowery Curtis L , Siegel Eric R , Eswaran Hari 
Published: October 2020

Abstract

Objective: Fetal magnetocardiography (fMCG) is a non-invasive biomagnetic technique that provides detailed beat-to-beat fetal heart rate analysis, both in normal rhythm as well as in fetal arrhythmias. New cryogenic-free sensors called optically pumped magnetometers (OPMs) have emerged as a less expensive and more geometrically flexible alternative to traditional Superconducting Quantum Interference Device (SQUID) technology for performing fMCG. The objective of the study was to show the ability of OPMs to record fMCG using flexible geometry while seeking to preserve signal quality, and to quantify fetal heart rate variability (FHRV). Approach: Biomagnetic measurements were performed with OPMs in 24 healthy pregnant women with uncomplicated singleton pregnancies between 28 and 38 weeks gestation (GA). A total of 96 recordings were analyzed from OPM data that was collected using sensors placed in two different maternal configurations over the abdomen. The fMCG signals were extracted and the quality of the recordings were quantified by peak amplitudes and signal-to-noise ratio (SNR). R peaks were used to perform both time and frequency domain FHRV analysis. FHRV measures obtained from OPMs were compared descriptively to the same measures obtained from GA-matched existing SQUID data. Main results: The fMCG derived from OPMs were observed in 21 of the 24 participants. Higher detection rates (85%) of fMCG signals were observed in the data sets recorded at GA >32 weeks. Peak amplitudes and SNR values were similar between two maternal configurations, but peak amplitudes were significantly higher (p = 0.013) in late GA compared to early GA. FHRV indicators were successfully extracted and their values overlapped substantially with those obtained from SQUID recordings. Significance: Taking advantage of the geometric flexibility of the OPMs, we have demonstrated their ability to record and quantify fMCG in different maternal positions as opposed to rigid SQUID configurations.
Deuterium retention characteristics in Li film by coating and during flowing liquid Li limiter operation in experimental advanced superconducting tokamak
Authors: Li C L , Zuo G Z , Maingi R , Cao Bin , Xu W , Meng X C , Sun Z , Huang M , Tang Z L , Zhang D H , Qian Y Z , Andruczyk D , Tritz K , Hu J S 
Published: October 2020

Abstract
Lithium (Li) is a promising low-Z material for particle recycling and impurity control to improve plasma performance in fusion devices. In the experimental advanced superconducting tokamak (EAST), Li coating has become a routine method for wall conditioning, and a flowing liquid Li (FLiLi) limiter has been successfully tested several times. Deuterium retention characteristics in the Li film coated on the international thermonuclear experimental reactor-like tungsten divertor and FLiLi during plasma discharges, which is important for the utilization of Li in future fusion devices, were investigated in EAST. It is found that the absorption of the fuel particles by Li coatings decreases gradually, and recycling gradually increases over a series of discharges. The maximum net amount of deuterium retained reached ∼0.8 g, corresponding to 12% deuterium in the Li. This corresponds to a whole day’s worth of shots with a total of 87 plasma discharges and a total of ∼640s plasma time after 11.75 g Li was deposited. Compared to the Li coating, it is shown that FLiLi continuously traps fuel particles and achieves a higher deuterium retention ratio over both the short- and long-term, leading to lower recycling. Meanwhile, it is also observed that the fuel particle retention ratio increases when FLiLi is closer to the plasma. This result is likely due to higher plasma heating power and limiter temperature, which cause an increased Li efflux from FLiLi due to a higher limiter temperature, which then redeposits on the other plasma-facing surfaces and increases fuel particle absorption. It is estimated that ⩾80% of the retained D particles are captured by the continual renewal of the Li redeposition film during the FLiLi operation. This investigation would also be useful for D/T retention in future fusion devices if Li is used as a plasma-facing component.
Multifunctional photonic broadband RF memory for complex electronic jamming
Authors: Ding Zhidan , Yang Fei , Zhao Jiejun , Wu Rui , Cai Haiwen , Wang Mingjun , Weng Yongxiang , Zhao Zixin 
Published: October 2020

Abstract
A multifunctional photonic broadband RF memory structure is presented to adapt to more and more complex electronic jamming scenarios. Based on precise sequence control of the structure with integration of switching and amplification functions at the output end, the response time of the structure is greatly reduced to 30 ns. Moreover, multiple jamming modes including reconfiguration of Doppler frequency shift (DFS), instantaneous bandwidth (IBW), center frequency, pulse width, storage time and pulse number are realized based on a coherent DFS structure with tunable optical filter and a memory structure with Vernier effect. The tuning range of DFS is greater than ±9 MHz, the reconfiguration range of IBW is 1.5 GHz–11 GHz, the tuning range of center frequency is 6.5 GHz–17 GHz, the maximum storage time of 100 ns–10 µs RF pulse signals is 750 µs, and the maximum number of stored RF pulses is 2500.
Validation of virtual resection on intraoperative interictal data acquired during epilepsy surgery
Authors: Demuru Matteo , Zweiphenning Willemiek , van Blooijs Dorien , Eijsden Pieter Van , Leijten Frans , Zijlmans Maeike , Kalitzin Stiliyan 
Published: October 2020

AbstractObjective. A ‘Virtual resection’ consists of computationally simulating the effect of an actual resection on the brain. We validated two functional connectivity based virtual resection methods with the actual connectivity measured using post-resection intraoperative recordings.Approach. A non-linear association index was applied to pre-resection recordings from 11 extra-temporal focal epilepsy patients. We computed two virtual resection strategies: first, a ‘naive’ one obtained by simply removing from the connectivity matrix the electrodes that were resected; second, a virtual resection with partialization accounting for the influence of resected electrodes on not-resected electrodes. We validated the virtual resections with two analysis: (1) we tested with a Kolmogorov-Smirnov test if the distributions of connectivity values after the virtual resections differed from the actual post-resection connectivity distribution; (2) we tested if the overall effect of the resection measured by contrasting pre-resection and post-resection connectivity values is detectable with the virtual resection approach using a Kolmogorv-Smirnov test.Main results. The estimation of post-resection connectivity values did not succeed for both methods. In the second analysis, the naive method failed completely to detect the effect found between pre-resection and post-resection connectivity distributions, while the partialization method agreed with post-resection measurements in detecting a drop connectivity compared to pre-resection recordings. Our findings suggest that the partialization technique is superior to the naive method in detecting the overall effect after the resection.Significance. We pointed out how a realistic validation based on actual post-resection recordings reveals that virtual resection methods are not yet mature to inform the clinical decision-making.
Creation of virtual channels in the retina using synchronous and asynchronous stimulation—a modelling study
Authors: Song Xiaoyu , Guo Tianruo , Shivdasani Mohit N , Dokos Socrates , Lovell Nigel H , Li Xinxin , Qiu Shirong , Li Tong , Zheng Shiwei , Li Liming 
Published: October 2020

Abstract

Objective. The spatial resolution of an implantable neural stimulator can be improved by creation of virtual channels (VCs). VCs are commonly achieved through synchronized stimulation of multiple electrodes. It remains unknown whether asynchronous stimulation is able to generate comparable VC performance in retinal stimulation, and how VC can be optimized by re-designing stimulation settings. This study begins with exploring the feasibility of creating VCs using synchronous and asynchronous epiretinal stimulation, and ending with predicting the possible VC performance with a thorough exploration of stimulation parameter space. Approach. A computational model of epiretinal dual-electrode stimulation is developed to simulate the neural activity of a population of retinal ganglion cells (RGCs) under both synchronous and asynchronous stimulation conditions. The interaction between the electrode and RGCs under a range of stimulation parameters are simulated. Main results. Our simulation based on direct RGC activation suggests that VCs can be created using asynchronous stimulation. Two VC performance measures: 1) linearity in the change in centroid location of activated RGC populations, and 2) consistency in the size of activated RGC populations, have comparable performance under asynchronous and synchronous stimulation with appropriately selected stimulation parameters. Significance. Our findings support the possibility of creating VCs by directly activating RGCs under synchronous and asynchronous stimulation conditions. This study establishes the fundamental capability of VC creation based on temporal interactions within the RGC population alone and does not include the effects of potential indirect activation of any surviving inner retinal network neurons. Our results provide theoretical evidence for designing next-generation retinal prosthesis with higher spatial resolution.
Screening Anti-MRSA Activities of Indigenous Microbes and Prediction of The Biosynthetic Gene Clusters
Authors: Asnani A , Amaliyah R , Yuniaty A 
Published: October 2020

Abstract

Methicillin-Resistant Staphylococcus aureus (MRSA) is a species of S. Aureus, which shows resistance to the methicillin class of antibiotics. MRSA infection poses significant health problems because it causes severe disease in a vulnerable population and also because effective antibiotics are limited. Therefore, the research to find the new anti-MRSA compound is a necessity. The genome mining approach through Biosynthetic Gene Clusters (BGC) analysis can detect the ability of microbes to produce antibiotics. Thus, the study aimed to screen potential anti-MRSA microbes and predict their BGC. This study used ten microorganisms isolated from mangrove areas in Segara Anakan Cilacap and clinical MRSA 2983 from the Faculty of Medicine, UNSOED. All samples microorganisms were cultivated in starch casein nitrate agar. DNA isolation used Quick-DNA Fungal/Bacterial Miniprep Kit, 16S rRNA gene amplification used 27F and 1492R primers, and DNA amplicons were sequenced by the Sanger sequencing method. BCG prediction of the associated genes used antiSMASH 5.1.2. The results showed that W-5A, P-6B, and W-5B isolates have anti-MRSA activities with inhibition indexes of 0.58; 0.53; and 0.47, respectively. Species identification revealed similarity of W-5A with Streptomyces longisporoflavus strain Moghannam M1, P-6B with Ochrobactrum intermedium LMG 3301, and W-5B with Streptomyces cellulosae strain NBRC 13027. The results of BGC analysis showed that Streptomyces longisporoflavus has one region involved in the synthesis of tetronasin. Ochrobactrum intermedium has one region involved in the synthesis ambactin. Streptomyces cellulosae has eight gene clusters for tiacumicin B, actinorhodin, ulleungmycin, albaflavenone, desferrioxamine B/E, stenothricin, auricin, and prejadomycin productions. These results indicate that the microbes isolated from Segara Anakan Cilacap serve as promising antibacterial producers.
Smart Development of Big Data App for Determining the Modelling of Covid-19 Medicinal Compounds Using Deep AI Core Engine System
Authors: Cholissodin I , Sutrisno S , Santoso N , Soebroto A A , Hidayat N , Rochman N T 
Published: October 2020

Abstract
Smart Big Data App Using Deep Artificial Intelligence (AI) Core Engine System focuses on solving problems related to the difficulty in building a prototyping model computer simulation like in silico as a model initiation of the complex Covid-19 medicinal compound involving Big Data ecosystems such as Hadoop and Spark. The difficulty is for example, currently, it is still very arduous to measure the rate of mixture of a compound when combined with many other compounds, which can consider the trade-off in minimizing the negative effects but optimizing the positive effects. In addition, the computation time becomes very long when using a system that is not in the Big Data ecosystem since this is proportional to the large number of compounds that vary widely and also the number of different situations of Covid-19 patients with other congenital diseases (comorbid) or without congenital disease; thus, it can be considered to be included in a condition that requires a very complex computational process which is very difficult to model using a conventional mathematical approach because the calculations are certainly very complex when compared to approaches using meta-heuristics algorithms such as Particle Swarm Optimization (PSO) which is much easier but requires a very large particle population space and iterative process to achieve global convergence. As a consequence, it requires fast computation processes based on distributed computing such as using the Big Data ecosystem. From the review of these problems, the system was created based on the Computational Intelligence; hence, the end-users, especially the developers, can build an application easier in spite of the complex computations, one of the which is in the meta-heuristic technique to minimize the negative effects and optimize the positive effects of the medicinal compounds by including a lot of data to get a better modeling. Therefore, the prototyping modeling project can be quick and robust, and achieve high performance measurements.
In vitro and In silico Analysis of Pomegranate (Punica granatum L.) Fruit Powder as Pancreatic Lipase and α-Amylase Inhibitor
Authors: Dewi Andi Alfira Ratna F , Muntholib  , Subandi  
Published: October 2020

Abstract
This study aims are to produce pomegranate powder, then to extracted with boiling water and to find out the phytochemical compounds, total phenolic compounds (TPC), total flavonoid compounds (TFC) and its inhibitory activity against pancreatic lipase by in vitro analysed. Besides of that, a compound that exist in pomegranate will also be in silico analysed by docking technique, for its binding with the α-amylase enzyme compared to acarbose. In vitro inhibition tests were conducted by titrimetric method, using olive oil as substrate, pancreatic lipase as enzymes, and orlistat as a standard inhibitor; meanwhile the in silico test was conducted by molecular docking techniques using human α -amylase as a receptor and acarbose and a compound in pomegranate (quercetin) as ligand. The result has shown that hot water extracts of pomegranate fruits powder (1.5 gr/150 ml) contained flavonoids, polyphenols, and alkaloids and TPC and TFC contents were 2.090 ppm and 2.058 ppm, respectively; had pancreatic lipase inhibition activity of 0.54 times compared to orlistat at the same mass (120 mg), and based on its molecular docking, quercetin, a compound in the pomegranate can bind to the α-amylase enzyme in a position that is relatively the same as acarbose, even with slightly larger affinity bindings.
The cyanidin-3-O-glucoside of Black Rice inhibits the interaction of HMG-CoA and HMG-CoA Reductase: three-and two-dimension structure
Authors: Fatchiyah Fatchiyah , Meidinna Hazna Noor , Suyanto Eko 
Published: October 2020

Abstract
The hypercholesterolemia condition is one metabolic disorder has affected to onset and prevalence of the dyslipidemia and cardiovascular disease. The cholesterol synthesized from HMG-CoA by co-enzyme HMG-CoA reductase. The research focus was to determine the effect of Cyanidin-O-glucose of black rice to prevent the HMG-CoA and HMG-CoA reductase interaction. The anthocyanins retrieved from the database of PubChem, is cyanidin-3-O-glucoside (CID: 12303221). We obtained HMG-CoA canonical SMILES (CID: 445127) from PubChem and reconstructed it using VEGAZZ software. RCSB Protein Data Bank (PDB) was used as a database to get the 3D structures of HMGR (PDB ID: 1DQ9). The water molecules and or previously existing ligands incorporated in their 3D structures were removed using Discovery Studio 2019. The docking results were visualized and analyzed by Discovery Studio, and Hex 8.0.0 software. This result determined that cyaniding-O-glucose of black rice prevented the interaction between HMG-CoA into HMG-CoA reductase respectively. This result indicates that the cyaniding-O-glucose of black rice has potential function as lowering cholesterol biosynthesis.
Effects of Dietary Brown Rice on Carcass Composition and Nitric Oxide (NOx) Metabolite Levels in High-Fat High-Fructose Diet-induced Sprague Dawley Rats as Obesity Model
Authors: Handayani Dian , Ramadhan Ahmad , Anindyanti Risma Debby , Innayah Alma Maghfirotun , Sulistyowati Etik , Kusumastuty Inggita 
Published: October 2020

Abstract
Obesity is characterized by excessive accumulation of fat in the body, which causes changes in body composition and endothelial dysfunction due to impaired production of nitric oxide (NO). The common means of managing obesity is through functional food, such as brown rice, which has high fiber and antioxidant content. Therefore, the purpose of this study was to determine the effect of adding brown rice to feed on carcass composition and NOx levels in obese rats. This was an experimental study involving male Sprague Dawley rats placed in 5 groups, in which 4 were allowed to turn to obese rats with the remaining one group as control. These 4 groups were allowed to later feed on high-fat high-fructose (HFHF) diet while the control fed on the normal AIN-93 diet, followed by 8 weeks of HFHF intervention and brown rice in feed with 3 different doses; 12.43%; 24.86%; and 37.29%. The serum NOx levels were analyzed by the Griess Reaction method, while the percentage of protein and fat was analyzed through Gravimetric Extraction. The results showed that the addition of brown rice resulted in changes in the Lee index (p = 0.000) and abdominal circumference (p = 0.000). Also, a correlation was observed between the Lee index and abdominal circumference (p = 0.001; r = 0.558) of rats. However, there was no significant difference between NOx and carcass protein levels, and there was an increase in carcass fat levels due to an increase in mitochondrial energy efficiency and resistance to protein synthesis in obese rats.