bluuebunny/crossref_metadata_2025_split huggingface dataset:
High-throughput dissection of the thermodynamic and conformational properties of a ubiquitous class of RNA tertiary contact motifs
Authors: Bonilla Steve L. , Denny Sarah K. , Shin John H. , Alvarez-Buylla Aurora , Greenleaf William J. , Herschlag Daniel 
Published: August 2021

Significance
We would like to have a predictive understanding of how RNAs form and interconvert between intricate three-dimensional shapes that are essential to function. Despite great structural diversity, RNAs are built from a limited set of structural motifs so that a predictive model may arise from the in-depth understanding of these building blocks. We used a quantitative, high-throughput approach to investigate the thermodynamic and conformational properties of the tetraloop/tetraloop receptor (TL/TLR), a ubiquitous RNA tertiary contact motif. Our investigation of 1,493 TLRs and two TLs revealed classes of TL/TLR thermodynamic behavior. One class displayed conserved conformation across sequences and appears to be thermodynamically selected in biology. Other classes are conformationally diverse and may be selected for flexibility instead of stability.
Power and efficiency scaling of Er: ZBLAN fiber laser
Authors: Newburgh G A , Dubinskii M 
Published: August 2021

Abstract
We report on a 976 nm pumped erbium doped fluoride (Er:ZBLAN) fiber laser emitting at 2.8 µm with nearly 70 W of output power in a quasi-continuous wave (Q-CW) regime with the slope efficiency versus launched pump power of ∼20%. It is believed to be the highest Q-CW power ever demonstrated from an Er:ZBLAN fiber laser . We also present the results of a study demonstrating that the Er:ZBLAN fiber laser slope efficiency versus absorbed pump power increases monotonically with the pump wavelength from 19% to 29% over the wavelength range of 960–985 nm. The achieved slope efficiency of 29% is, to the best of our knowledge, the highest efficiency ever reported for an Er:ZBLAN fiber non-cascaded laser.
Rainfall Prediction In Nagapattinam Using Fuzzy Logic
Authors: Santha S. , Brindha Devi M. K. 
Published: August 2021

Abstract
Rainfall plays a vital role in human life rather than other weather events. As the variations are unpredictable, it difficult to predict rainfall over a region, so that rainfall forecasting carried out by the metrological department has been most crucial and demanding one. Fuzzy logic models have been proposed to perform forecasting, and its prime operations are fuzzification and defuzzification. These models are simple to employ but offer better results than statistical models. The present study explores the strength of forecasting models based on fuzzy logic rules. Furthermore, predicted results are compared with the actual rainfall data.
Thermodynamics of Regular Black Holes Inspired by Noncommutative geometry Journal of Physics: Conference Series
Authors: Singh B K , Singh R P 
Published: August 2021

Abstract
We present a new, exact, solution of regular Schwarzschild black hole by introducing an anisotropic perfect fluid inspired by noncommutative geometry. The obtained solution is interpolated between two quantities which are the de Sitter space-time at little distance and the regular Schwarzschild geometry at extensive extent. The consequence of noncommutative geometry is that it alters the thermodynamical characteristics of the black hole. Hawking temperature is calculated and its graphical study affirms striking features with reference to the alteration of the Hawkins temperature with the petty radius of the black hole.
Radio Mean Labeling of Some Splitting Graphs
Authors: Palani K. , Sabarina Subi S.S. , Maheswari V. 
Published: August 2021

Abstract
Let G = (V, E) be a simple graph with p vertices and q edges. For a connected graph G of diameter d, a radio mean labeling is a one to one mapping f from V(G) to N satisfying the condition

d
(
u
v
)
+
[

f
(
u
)
+
f
(
v
)

2

]
≥
1
+
d
i
a
m
(
G
)

for every μ, ν ∈ V (G). The span of a labeling f is the maximum integer that f maps to a vertex of G. The radio mean number of G, r
m
n(G) is the lowest span taken over all radio mean labelings of the graph G. In this paper, we analyze some splitting graphs for radio mean labeling.
q Sets in μNTopological Spaces
Authors: Hari Siva Annam G. , Raksha Ben N. 
Published: August 2021

Abstract
In this article, q sets in μ

N
TS are to be introduced and their basic properties are to be discussed. Some operators of the q Sets in μ

N
Topological Spaces such as μ

N

q Frontier, μ

N

q Exterior, μ

N

q Border are to be introduced and their characters are to be contemplated.
Effect of anisotropy pores on thermohaline convective instability in micropolar ferrofluid
Authors: Ratchagar Nirmala P , Seyalmurugan S. 
Published: August 2021

Abstract
This work deals with the thermohaline convective instability on horizontal micropolar ferrofluid layer in anisotropic porous effect subjected to a transverse uniform magnetic field. The linear stability analysis is used to omit the non-linear terms on governing equations, normal mode analysis is taken to the study and free boundary conditions are applied. The critical magnetic thermal Rayleigh number N

SC
is calculated analytically for sufficient large values of M
1 The principle of exchange of stabilities is satisfied for micropolar ferrofluid in an anisotropic porous medium without N
1, N
’
3, N
’
5 and τ. The sufficient conditions for the non-existent of overstability are also examined. Moreover, in this work, we tried to investigate the anisotropy effect on porous medium on the system. The parameters N
1and N
5
’ dominate the system and the large porous medium is taken into account.
Identity Protection during the use of Internet
Authors: Agrawal Navin Kumar 
Published: August 2021

Abstract
In today’s era, security become important concern. As we are moving towards the digitalization data protection is important issue. To make the data as well system safer we must follow some simple but important steps. These steps works just as safe guard. The concern regarding use of internet become more when we are making digital payment or sharing some useful information. More awareness is also required in case of non-technical person whenever use the internet. In this era technology is reachable to every person. We also execute many financial activities through our mobile / Computer. So many observers are there who are regularly keeping any eye on our activities and never miss our single loophole. Some simple Dos and Don’ts can make the difference and create awareness in the society.
Scientific Exploration for Density Estimation and Crowd Counting of Crowded Scene
Authors: Singh Juginder Pal , Kumar Manoj , Arya Ayush , Baldev  , Badmera Bharat 
Published: August 2021

Abstract
Crowd density estimation model is a typical concept which compute the counting of the people in the crowded image. There are many of research papers are written in this area to solve the different kind of real world problems. This paper shows the state of art and different types of framework proposed on density estimation and crowd counting techniques. The population of our country increases year by year, so the purpose of this paper is to explore different techniques available for crowd density estimation. There are lot of applications existing based on this technique like retail system, surveillance system etc., where the foot traffic is very vital in retail system to organize merchandise in aisles, optimize store layout, understand peak times and potentially even protect against theft. In surveillance system, this is mainly used for security purpose. In this, the researcher captures the crowd using the camera and the technique of counting the crowd which is divided into two parts unsupervised and supervised learning. These techniques are further divided into parts which is shown in the paper. The survey presents the different types of datasets of the crowded image which is useful for simulating the people counting in the crowded scenes. In detection based approach, this technique counts the people with the help of face detection technique. In this researchers face the problems of count the people in crowded scenes and also face the problem in surveillance applications. The cluster based approach data works well on the scattered crowd. This method needs image frames; it does not work on still images. In regression approach the model trained is subject to the point of view map. In the model were to be used in a different scene of a changed perspective map, it will have many inaccuracies in its result. The current research work intends to provide a general idea on crowd density estimation and counting approaches employed in visual surveillance in the perception of the study of computer vision. The analysis of review categorizes and frameworks quite a lot approximation related to crowd density and calculating approaches which are beneficial in providing the analysis related to the crowd places of interest.
Symmetric bi-interior ideals of Symmetric Semigroups
Authors: Punitha Tharani A. , Uma Maheswari V. 
Published: August 2021

Abstract
In this paper, as a further generalization of ideals, we introduce the notion of symmetric bi-interior ideal as a generalization of symmetric quasi ideal, symmetric bi-ideal and symmetric interior ideal of symmetric semigroup and study the properties of symmetric bi-interior ideals of symmetric semigroup and simple symmetric semigroup.
Product-Set Labeling of Some Zero-Divisor Graphs and its Line Graph
Authors: Rajeswari R. , Aruna Sakthi K. , Meenakumari N. 
Published: August 2021

Abstract
Let G = (V, E) be a graph with p vertices and q edges. A graph has product-set labeling if there exist an injective function f: V(G) → P (N) such that the induced edge labeling function f
∗: V(G) → P(N) is defined as f
∗ (μ
ν) = f (μ) ∗ f (ν) ∀μ, ν ∈ E(G).f (μ) ∗ f (ν) = {ab: a ∈ f (μ), b ∈ f (ν) }. In this paper we investigate how product-set labeling works for the zero-divisor graph and line graph of zero-divisor graphs.
A Pre-Trained Vs Fine-Tuning Methodology in Transfer Learning
Authors: Gupta Neeraj 
Published: August 2021

Abstract
Transfer learning from a pre-trained and fine-tuning methodology has been utilized for the image classification. In this paper, we classify images of cats and dogs. It is much faster and easier than training from scratch using a pre-trained network with transfer learning. This saved network was trained previously on a huge dataset and known as a pre-trained model. The pre-trained model can be used in two ways, either it is used in the same way or it utilizes transfer learning approach to adapt this pre-trained network to a specific goal. Since the idea for image classification using transfer learning is that it is trained on the general and large dataset and further this model will be efficiently worked on the visual perception task of the real world. In fine-tuning, instead of tuning with the weights of generic feature map of based model, it is tuned accordingly to the dataset. In this paper, we take benefit of these learned feature maps deprived of having to start from scratch by utilizing a deep learning technique on a huge dataset and analyze the various methodology. The experimental results show that fine-tuning methodology outperformed over the pre-trained with feature extraction on accuracy.
Sign Pairity Difference Cordial Labeling of Digraphs
Authors: Palani K. , Nivetha S. , Nagarajan A. 
Published: August 2021

Abstract
Let D = (V, A)be a digraph. An injective function f: V(D) → {1,2, …. p} is said to be a sign pairity difference cordial labeling if the induced arc labeling f
∗: A(D) → {0,1} defined byf
∗ ((μ, ν)) =

{

1

iff
(
u
)
−
f
(
v
)
>
0

0

elsewhere

satisfiesthe condition that |e

f
0-e

f
(1)| ≤ 1 where, e

f
(0) is the number of arcs with label 0 and e

f
(1) is the number of arcs with label 1. In this paper, we analyze the existence of sign pairity difference cordial labeling in the digraphs Directed Path

(

P
n

→

)

(
A

P

n

→

)

, Directed Cycle

(

C

n

→

)

, Outstar

(
o

K

1
,
n

→

)

, Inwheel

(
i

W

n

→

)

and Downcomb

(
Down

P

n

⊙

K

1

→

)

defined by K.Palani et.al.
Neighborhood Prime Labeling in Some Product And Power Digraphs
Authors: Palani K , Shunmugapriya A , Meenakumari N 
Published: August 2021

Abstract
Let D(p, q) be a digraph. A function f: V → {1, 2, …, n} is said to a neighborhood prime labeling of D if it is both in and out degree neighborhood prime labeling. In this paper, we introduce the concept of neighborhood prime labeling in digraphs and also investigate the existence of neighborhood prime labeling in some digraphs.
Minimal Bi-Ideal of Г-Near Subtraction Semigroups
Authors: Meenakshi P. , Meenakumari N. 
Published: August 2021

Abstract
In analogy with the concept of bi-ideal of Γ-near subtraction semigroups, we introduce the notion of minimal bi-deal of Γ-near subtraction semigroups. In this paper, we obtain a necessary and sufficient condition for a zero-symmetric Γ-near subtraction semigroup to be a Γ-near – field. Further we have proved some properties of minimal bi-deal of Γ-near subtraction semigroupsand its characterization theorems.
Sinusoidal Fuzzy Soft Set and its Application in Mcdm
Authors: Karthika R. , Sahaya Sudha A. 
Published: August 2021

Abstract
This paper deals with the study of extension of classical soft sets into a Sinusoidal fuzzy soft set based on Sinusoidal fuzzy number and the basic operations on a sinusoidal fuzzy soft set are defined. Then a new algorithmic approach for Multi Criteria decision making based on Sinusoidal fuzzy soft set has been furnished using the ranking techniques, finally it has been analyzed in detail and illustrated with a numerical example.
A Ophthalmology Study on Eye Glaucoma and Retina Applied in AI and Deep Learning Techniques
Authors: Vaishnavi S. , Deepa R. , Nanda kumar P. 
Published: August 2021

Abstract
Artificial intelligence based on deep learning has huge global interest in current times. Deep Learning has been widely affiliated in image and speech recognition and also natural language processing, but it is beginning of healthcare. In ophthalmology, Deep learning has applied in photographs fundus, optical coherence tomography and vision sectors. Accomplishes safety in classifying the detection performance on diabetic retinopathy, age-related macular degeneration. Deep learning may be used in concurrence with telemedicine as possible to diagnose and monitor major eye diseases for patients in primary care. There are also prospective challenges with Deep learning application in ophthalmology, including clinical and technical challenges, explain ability of the algorithm results, medico legal issues, and physician and patient acceptance of the AI “black-box” algorithms. Deep learning could probably revolutionize how ophthalmology is practiced in the future. Hence this reviewprovides a Deep Learning systems described for ophthalmic conditions, and fundamental functions.
Selection Of Best Social Media Using Group Decision With Picture Fuzzy Graphs
Authors: Priyanka R. , Preethi Ceon Y. 
Published: August 2021

Abstract
In this dissertation, we study the picture fuzzy graph (PFG) in the decision-making problem based on picture fuzzy relation and some types of picture fuzzy graphs such as complete picture fuzzy graphs, strong picture fuzzy graphs, complement picture fuzzy graphs are described and also study the Pythagorean fuzzy graph in decision making environment. Further, we present an application of Pythagorean Fuzzy Graphs and Picture Fuzzy Graphs in decision making environment.
Stability Enhancement of DFIG Based Wind Turbine Under Three Phase Fault with STATCOM
Authors: Lakshmi Priya J , Jaya Christa S.T 
Published: August 2021

Abstract
The main aim of this paper is to improve the transient stability of Doubly Fed Induction Generator (DFIG) based wind turbine using Static Synchronous Compensator (STATCOM). In this paper, a multi-objective problem is formulated to minimize voltage deviations at the point of common coupling (PCC) and mitigate low frequency oscillations after clearing the faults. Genetic algorithm based STATCOM controller is used to enhance the stability of a grid-connected wind farm composed of a variable-speed wind turbine generator system (WTGS). The transient performance of the proposed control scheme is analyzed with a three-phase fault. The Simulations are carried out in MATLAB/Simulink environment.
Experimental Study of Adsorption Efficiency of Methylene Blue Dye by Using Banana Leaf Biochar as an Adsorbent
Authors: Kumar Umesh , Vibhute Bhalchandra , Parikh Sachin 
Published: August 2021

Abstract
Removal of dye from wastewater has been a matter of concern, both as health point of view and in aesthetic sense. Colour removal from dye wastewater has been given much attention, not only because of its toxicity and water problem, but also mainly due to its visibility problem. There have been various promising techniques for the removal of dye from effluent. However, the adsorption effectiveness for dye removal from waste water has made it an ideal alternative to other expensive treatment methods. Agricultural wastes are inexpensive, biodegradable. Agricultural wastes are excellent sources for the production of adsorbent, which can be used as alternate, low cost treatment systems for the dye generated during the textile processing. Biochar was prepared by activating banana waste and used as an effective bio-sorbent to remove methylene blue (MB) dye from aqueous solution. Batch adsorption experiments are carried out using banana leaves as adsorbent. The adsorption study was performed by varying the adsorption parameter such as pH, adsorbent dose, contact time, temperature, agitation speed, and adsorbent particle size.
Treatment of Textile Wastewater Using Sodium Alginate Beads
Authors: Sharmila A , Mardera Madhumathi S , Soundarya H P , Shreyas M 
Published: August 2021

Abstract
Textile is one of the important industry. Conversion of fiber to fabric takes place which involves many process and synthetic chemicals. The fabric is then dyed or printed, fabricated into clothes. The extraction of dyes from the wastewater industry becomes a worldwide issue. Water contamination due to industrial discharge is the big threat to the environment. Hence an attempt was made in this study to treat textile wastewater using natural anionic polysaccharide sodium alginate as adsorbing agent. The optimum condition was obtained by varying dosage, pH, flow rate and depth of beads for varying contact time. For optimum conditions, the textile wastewater was analyzed. Results showed 32%, 56% and 75% removal of sulphates, alkalinity and nitrates respectively. Hence sodium alginate proved efficient in treatment of textile wastewater.
A Glimpse on Possible Detection Tools and Vaccines for Mitigation and Management of COVID-19
Authors: Rajasulochana P. , FahiraTasneem S. , Kapoor Ashish , Chandan Monit Kumar 
Published: August 2021

Abstract
The world is made up of all kinds of living organisms which also includes microorganisms like bacteria, virus and fungus. One of them coronavirus was rare one but in 2019, a new strain called SARS-CoV-2 was discovered in Wuhan, China which was quite similar to SARS-CoV Virus. Days went and the world was in pandemic. The virus, subsequently named COVID-19 virus was affecting all over the world and lives were in peril. People got aware of its symptoms and precautions declared by World Health Organization (WHO). COVID-19 was mainly diagnosed by RT-PCR and antigen tests. After crossing many hurdles, scientists developed vaccines and some of them like Comirnaty, mRNA-1273 and AstraZeneca vaccines got approved by FDA and it was developed by many premier institutes. So far, at least 5.9 million people in United States have received their first dosage and other vaccines are under clinical trials. This review provides a glimpse on various aspects related to COVID-19 including diagnostic tools and vaccination
Comparative Analysis Of In Vitro Antidiabetic Activity Of Wild And Micropropagated Solanum Trilobatum L
Authors: Rajasulochana P. , Battineni Abhigna , Fahira Tasneem S. 
Published: August 2021

Abstract
Diabetes is metabolic disorder which is characterized by an increase in glucose level due to a relative deficiency of insulin. Recent decades have experienced a very high prevalence of diabetes mellitus. One way of treating diabetes is to reduce gastrointestinal glucose production by inhibiting carbohydrate digesting enzymes called pancreatic alpha-amylase and intestinal alpha-glucosidase. The present study aims to compare the efficacy of wild and micropropagated Solanum trilobatum for its in vitro antidiabetic property. Solanum trilobatum grown in vitro under aseptic conditions was compared with wild-grown, and the results have revealed that both wild and micropropagated plants have effective dose-dependent inhibition of alpha-amylase and alpha-glucosidase enzyme. For both alpha-amylase and alpha-glucosidase assay micropropagated plant has shown lesser efficacy at all concentrations when compared to that of wild grown. still micropropagated showed effective inhibition with nearly 90% similarity.
A Mathematical Modelling of A Multi-Physics Ensemble Approach for Exploring the Sensitivity of Climate
Authors: Gupta Raj Kumar , MagnoVentayen Randy Joy , Saravanakumar R , Salahuddin Ghazal , Nomani M.Z.M. 
Published: August 2021

AbstractThe amount of global surface warming that will effectively respond to twice of atmospheric CO2 concentrations compared with pre-industrial levels is referred to as climate sensitivity. The aim to explore the sensitivity of climate by using the mathematical model of the multi-physics ensemble approach. It’s considered as a multi-physics MM5 ensemble of 30 years hindcast simulations run through a complicated and climatically varied area. In this study, eight multi-physics ensembles (MPEs) models were used, MIROC5 physics systems were replaced with MIROC3 physics systems. The analysis is based on a seasonal time scale with an emphasis on average temperature and precipitation values as well as interannual variability. Multi-parameter MPE was made a set ensemble of perturbed-physics in which the parameter value for individual MPE model is swept. The previously evaluated MPE approach can be better understand and improve in the simulation of the multi-physics climate by using Bayesian inference. Bayesian inference allows actions often associated with a post-model flexible project to be incorporated into the model development process. As a result, an ensemble of model configurations has been created, which allows for a more thorough assessment of the remaining uncertainties. The value of model physics is shown by demonstrating that the dispersion between experiments is comparable.
Battery Management System for E-Vehicle using Kalman Filter
Authors: Balachander K , Amudha A , Naveen KT 
Published: August 2021

Abstract
For safe and proper battery management system the main aspect is to do a optimization of SOC which is State-of-Charge estimation. This paper gives you the maximum achievement of BMS with the electric vehicle Lithium ion Battery. Kalman filter design is implemented in this in order to reduce the mechanical noise and further voltage and current ripples where the man aim of this research work using Kalman is that it must have some proper sequence like a proper electronics and electrical model to get rid of the noises and ripples, thus the models current state and its system design is verified where it can apply to all sorts of problems and can apply to all such current manufacturers. From this point of view, we implemented a design which matches the output source of Kalman filter design and takes the less time for giving the accurate output. Hence the simulation with the Kalman filter design and its respective needed electronics components are therefore simulated and programmed by the MATLAB Simulink.