bluuebunny/crossref_metadata_2025_split huggingface dataset:
Linear perturbations of Einstein-Gauss-Bonnet black holes
Authors: Langlois David , Noui Karim , Roussille Hugo 
Published: September 2022

Abstract
We study linear perturbations about non rotating black hole solutions in scalar-tensor theories, more specifically Horndeski theories. We consider two particular theories that admit known hairy black hole solutions. The first one, Einstein-scalar-Gauss-Bonnet theory, contains a Gauss-Bonnet term coupled to a scalar field, and its black hole solution is given as a perturbative expansion in a small parameter that measures the deviation from general relativity. The second one, known as 4-dimensional-Einstein-Gauss-Bonnet theory, can be seen as a compactification of higher-dimensional Lovelock theories and admits an exact black hole solution. We study both axial and polar perturbations about these solutions and write their equations of motion as a first-order (radial) system of differential equations, which enables us to study the asymptotic behaviours of the perturbations at infinity and at the horizon following an algorithm we developed recently. For the axial perturbations, we also obtain effective Schrödinger-like equations with explicit expressions for the potentials and the propagation speeds. We see that while the Einstein-scalar-Gauss-Bonnet solution has well-behaved perturbations, the solution of the 4-dimensional-Einstein-Gauss-Bonnet theory exhibits unusual asymptotic behaviour of its perturbations near its horizon and at infinity, which makes the definition of ingoing and outgoing modes impossible. This indicates that the dynamics of these perturbations strongly differs from the general relativity case and seems pathological.
Climate Change and Astronomy: A Look at Long-term Trends on Maunakea
Authors: van Kooten Maaike A. M. , Izett Jonathan G. 
Published: September 2022

Abstract
Maunakea is one of the world’s primary sites for astronomical observing, with multiple telescopes operating over submillimeter to optical wavelengths. With its summit higher than 4200 m above sea level, Maunakea is an ideal location for astronomy, with a historically dry, stable climate and minimal turbulence above the summit. Under a changing climate, however, we ask how the (above-)summit conditions may have evolved in recent decades since the site was first selected as an observatory location and how future-proof the site might be to continued change. We use data from a range of sources, including in situ meteorological observations, radiosonde profiles, and numerical reanalyses to construct a climatology at Maunakea over the previous 40 yr. We are interested in both the meteorological conditions (e.g., wind speed and humidity) and the image quality (e.g., seeing). We find that meteorological conditions were, in general, relatively stable over the period with few statistically significant trends and with quasi-cyclical interannual variability in astronomically significant parameters such as temperature and precipitable water vapor. We do, however, find that maximum wind speeds have increased over the past decades, with observed wind speeds above 15 m s−1 increasing in frequency by 1%–2%, which may have a significant impact on ground-layer turbulence. Further, we note that while the conditions themselves are not necessarily changing significantly, the combination of conditions that lead to dome closures (i.e., freezing conditions, increased summit wind speeds, and/or high humidities) are worsening to the point that the number of closure conditions have more than doubled in the last 20 yr. Importantly, we find that the Fried parameter has not changed in the last 40 yr, suggesting there has not been an increase in optical turbulence strength above the summit. Ultimately, more data and data sources—including profiling instruments—are needed at the site to ensure continued monitoring into the future and to detect changes in the summit climate.
Probing the Atmospheric Precipitable Water Vapor with SOFIA, Part III. Atlas of Seasonal Median PWV Maps from ERA5, Implications for FIFI-LS and in situ Comparison Between the ERA5 and MERRA-2 Atmospheric Re-analyses
Authors: Iserlohe C. , Vacca W. D. , Fischer C. , Fischer N. , Krabbe A. 
Published: September 2022

Abstract
The Stratospheric Observatory for Infrared Astronomy (SOFIA) is an airborne observatory for far-infrared astronomy stationed at the Armstrong Flight Research Center (AFRC) in Palmdale, CA, USA. Although SOFIA flies at altitudes of ∼41,000 ft, any far-infrared observations from within the Earth’s atmosphere are nevertheless hampered by water vapor absorbing the astronomical signal. The primary atmospheric parameter governing absorption in the far-infrared is the total upward precipitable water vapor, PWV. In this paper we present global PWV maps derived from re-analyses from the European Centre for Medium-Range Weather Forecasts, ECMWF, with a geographical resolution of 0.°5, for flight altitudes ranging from 37,000 ft to 45,000 ft and each meteorological season. These maps were validated with FIFI-LS PWV measurements on board SOFIA and allow an investigation of the global morphology and seasonal dependence of the total upward PWV in the stratosphere. We additionally investigate the observing conditions, in terms of PWV, at various locations, especially around SOFIA’s home base, Palmdale, but also around sites in the southern hemisphere like Tahiti, Santiago de Chile (Chile), Buenos Aires (Argentina), and Christchurch (New Zealand). From the southern sites investigated Christchurch provides the best conditions in terms of PWV (and efficiency), Tahiti the worst. Using total power sky measurements with FIFI-LS we also derive a mean emissivity of the telescope (primary, secondary and tertiary mirror) of ϵ
Tel = 20.5 ± 1.6% around the astronomically significant [C ii] emission line. We finally compare atmospheric re-analyses from GEOS (MERRA-2) and ECMWF (ERA5) to our FIFI-LS PWV measurements. Both re-analyses correlate linearly with our FIFI-LS PWV measurements from all flight altitudes but with different scaling factors. However, MERRA-2 correlates significantly less well than ERA5 especially for flight altitudes below 41,000 ft.
Identifying Transient Candidates in the Dark Energy Survey Using Convolutional Neural Networks
Authors: Ayyar Venkitesh , Knop Robert , Awbrey Autumn , Andersen Alexis , Nugent Peter 
Published: September 2022

Abstract
The ability to discover new transient candidates via image differencing without direct human intervention is an important task in observational astronomy. For these kind of image classification problems, machine learning techniques such as Convolutional Neural Networks (CNNs) have shown remarkable success. In this work, we present the results of an automated transient candidate identification on images with CNNs for an extant data set from the Dark Energy Survey Supernova program, whose main focus was on using Type Ia supernovae for cosmology. By performing an architecture search of CNNs, we identify networks that efficiently select non-artifacts (e.g., supernovae, variable stars, AGN, etc.) from artifacts (image defects, mis-subtractions, etc.), achieving the efficiency of previous work performed with random Forests, without the need to expend any effort in feature identification. The CNNs also help us identify a subset of mislabeled images. Performing a relabeling of the images in this subset, the resulting classification with CNNs is significantly better than previous results, lowering the false positive rate by 27% at a fixed missed detection rate of 0.05.
A gyro-fluid model of global geodesic acoustic modes supported by finite ion Larmor radius
Authors: Wang Yu , Zhou Tianchun , Wang Xiaogang 
Published: September 2022

Abstract
A theory of global geodesic acoustic modes with short wavelengths based on the framework of an electrostatic gyro-fluid has been developed, in which the more thorough sorts of finite-ion-Larmor-radius effects are encompassed than in the two-fluid model (Wang et al 2021 Nucl. Fusion
61 106024), while the radial differential equation of the eigenmodes still comes up in a compact and analytically tractable form. By solving the corresponding boundary value problem numerically with typical equilibrium profiles, a multitude of global geodesic acoustic modes with quantized eigen-frequencies have been found. In particular, as the consequence of the plasma model improvement, we have obtained multiple edge-localized global geodesic acoustic modes with the features resembling those observed experimentally.
Staircase formation by resonant and non-resonant transport of potential vorticity
Authors: Yan Qinghao , Diamond Patrick H. 
Published: September 2022

Abstract
The E × B staircase is a quasi-periodic pattern of pressure profile corrugations. In this work, we present a new mechanism for E × B staircase formation that involves resonant transport versus non-resonant transport. We start from a potential vorticity evolution system and use quasi-linear theory, a model dispersion relation, and a bi-Lorentzian spectrum approximation, to construct the relation between the fluxes and the profiles. With these fluxes, we close the profile evolution equations and the extended turbulence intensity evolution equation, which together constitute a turbulence-profile evolution system. In this system, the Doppler effect from the E × B mean flow can cause resonance between trapped ion precession motion and the trapped ion mode, which drives a resonant transport contribution to the fluxes. The profiles will be flattened where the resonant transport is switched on. In contrast, for the regions of non-resonant transport, profiles are steeper. A quasi-periodic pattern of profile corrugation (the E × B staircase) spontaneously emerges in this system, which is the two states mentioned above, arranged as alternating layers in space. The feedback processes during the staircase pattern formation are identified. An estimate of the critical value of the boundary heat flux is obtained, above which the staircase formation will be triggered. An estimate scaling of the step size in the staircase pattern is obtained. The resonant turbulent transport is also a mechanism for collisionless saturation of zonal flow. This work is related to internal transport barrier formation and suggests some new scenarios, such as an enhanced confined L mode.
Frequency Monitoring Analysis based Power Quality Operational Data Management System
Authors: SaiHimajaChowdary K. , Mantri Vijaykumar , Neelakantappa M. 
Published: September 2022

Abstract
In this work, a low-cost measurement solution (named PyFreqDAQ) has been developed to monitor the frequency of the electrical network, which is regarded a quality parameter of the electrical supply, and at the same time provide a more precise result thanks to the usage of the Allan variance. Software (Grafana) is available for free and can be used to track the frequency’s change over time in order to better understand how it is maintained within certain parameters. Two distinct techniques of calculating the frequency have been used to show the device’s power consumption. For starters, we’ll follow the guidelines established by IEC 61000-4-30 The Allan variance-based approach, on the other hand, uses an algorithm that offers a more precise frequency measurement and a GPS-traceable reference value. With the Allan variance-based method, one can expect improved precision and accuracy, as well as faster calculations and a wider range of observations. A significant advantage over other applications (e.g. labVIEWTM) is the flexibility demonstrated by Python while programming the data capture card and interacting with the database Because Python is a more powerful programming language, it allows for operations and calculations to be carried out using simple codes, while also allowing for minimal computational load and consuming considerably less working memory. To date, there hasn’t been any comparative research done between Python and LabVIEWTM.
Control Strategies for Improvement of Power Quality in Grid Connected Variable Speed WECS with DFIG – An Overview
Authors: Singh Pradeep , Arora Krishan , Rathore Umesh C. 
Published: September 2022

Abstract
The presented paper gives a detailed observation of the PQ related problems for WE based on the EFIG or DFIG (Extra or Doubly Fed Induction Generator. Fundamental Frequency Components are the most typical reasons of disruption of power quality. On the other hand, wind loading conditions also disrupt the power quality. Numerous modes for the removing of these problems were studied to get the rid of these fundamental frequency components of the WES (Wind Energy Systems). In the presented paper, there is substantial analysis of numerous controlling techniques were presented to eliminate these PQ and different loading conditions i.e. grid conditions and wind loading conditions. Furthermore, utilizing the WECS (Wind Energy Conversion System) as an operative filter. This analysis of DFIG based WECS help research scholars to choose the adequate control procedures while utilizing the WECS as an operative filter.
Optimal integration of renewable distributed generators and electric vehicles in a radial distributed network
Authors: Kumar V , Sudabattula S K , Dharavat N 
Published: September 2022

Abstract
With the rising interest in sustainable transportation efforts, the optimal integration of Electric Vehicles (EVs) in the transportation business has come into existence very drastically. However, because of the increased power consumption, their impact on the electric power market might result in more enormous losses in the active power, a reduced voltage profile, as well as reduced voltage stability limits. In Radial Distribution System (RDS), getting the reduced effect of EVs load is crucial. It is significantly important to build charging stations for EVs and Distributed Generators (DGs) at the best locations. This article presents a combined approach to solve the optimal integration of DGs and EVs problem. First, the desired locations of DGs and EVs are found using the Voltage Stability Index (VSI) method.
Further, the resource ratings are obtained by the Firefly algorithm (FA) method. EVs charging dump and smart charging strategies are used, and comparison is done with both systems. Furthermore, the main objective of this work is to reduce the power loss and maintain a good voltage profile at each bus in the RDS. Finally, the developed approach is tested on IEEE 69 bus system.
Power Efficient Technique for CMOS- Logic Circuits
Authors: Adhikari Manoj Singh , Sahil Shaik , Tarun Naidu Palatla Babasri , Roy Aseervadam Thushar , Devendra Mandapati , Goutham Uppala 
Published: September 2022

Abstract
Power outages on normal CMOS circuit is very high it can be reduced by using the adiabatic technique. Adiabatic technique is used in the pull up part of CMOS logic. Power loss of CMOS Logic is in terms of heat. Adiabatic is an efficient technique where some of the energy stored in the load and it is used for next inputs without dissipating as heat. The adiabatic technique depends largely on the parameter variation. With the help of DSCH, MICROWIND, TANNER EDA (S-edit, TWV, TSP) Software’s power consumed by ECRL (Efficient Charge Recovery Logic) is compared to the power consumed by common CMOS for NAND and NOR inverter circuits. In this study it is find out that the adiabatic technique is the good choice rather than conventional technique in terms of power consumption.
Collision Avoidance and Direction Planning for Autonomous Vehicles
Authors: Gannaram Nithish Kumar , Nayak Jitesh Kumar , Mahesh Sudarsi , Anil Pappala , Chikkala Vamsi , Kumar Nitin 
Published: September 2022

Abstract
The rapid development of information and signal processing technology has contributed significantly to the development of autonomous driving (AD) techniques, which improve driving safety while minimizing human efforts. According to analyst predictions, automatic cars will soon surpass manual cars in number as automatic driving becomes more sophisticated. Ensuring safety and reducing the road accidents is the primary concerns in automated vehicles. Recent research has shown that computer vision, deep learning, and other fields have advanced beyond the imagination. The paper covers the deep learning algorithms and techniques necessary to make a reliable and real-time collision avoidance system using concepts such as Convolutional Neural Networks (CNN), YOLOv4 (You Look Only Once), and other deep learning architectures while also reviewing the current state of the art strategies for Advanced Driver Assistance System (ADAS). By using CNN algorithms, it is possible to detect lane markings and signboards in real time as well as estimate distances between them.
Dual phenomenon of surface plasmon and laser optics induced EM enhancement for rapid DNA detection with semiconductor nanostructures (SiNWs/AgNPs)
Authors: Ramachandran Krithikadevi , Dauodi Kais , Columbus Soumya , Tlili Abdelaziz , Gaidi Mounir 
Published: September 2022

Abstract
Recently exploring bioanalytical instrumentation principles emphasized with combination of optics and EM fields in surface enhanced Raman spectroscopy (SERS). The principles favour the rapid detection of DNA with proper fabrication of SERS sensor. 1D semiconductor nanostructures (SiNWs) functionalization with plasmonic silver nanoparticles are fabricated by PLD process and exploited for SERS detection of DNA. The DNA nucleotide bands are indexed with reference to their Raman shift as Adenine (A), Guanine (G), Cytosine (C), Thymine (T) at Raman spectral regions of 1352 cm-1, 676 cm-1, 1625 cm-1, 1441 cm-1 respectively. The finest conditions for sensitive detection of DNA were investigated and their interaction mechanism are presented. The point-to-point reproducibility measurements imprinted higher degree of concordancy. The designed SERS sensor will be definitely helpful almost in all application fields with portable handheld Raman spectrophotometer in near future.
Disaster Monitoring based on IoT and Long Range Assisted Framework
Authors: Bagwari Swapnil , Roy Ajay , Singh Rajesh , Gehlot Anita 
Published: September 2022

Abstract
We encounter so many hazardous situations which effects living species and the materials they own. Due to natural calamities and environmental disasters, there is an increase in losses of lives and materials. Landslides are caused due to heavy rains, sloping of land because of earthquakes and deforestation. The research is about the preventive landslide detection and alerting system using various sensors and Arduino. The data collected by the sensors is transferred to Arduino which is further sent to NODEMCU through Lora module. The data obtained at NODEMCU will be transferred to database server for real-time monitoring and processing. Due improvement in the field of IoT systems has made the use of low cost, low power LoRA technologies to detect the environmental disaster and prevent from dangerous situations with less damage to living beings. In view to cover larger area with reduced costs and low power consumption, we used the LoRa technology for transmitting the monitoring data and Wi-Fi communication is used for sending the alerts. The processed data will be displayed on the mobile application interface.
Polymer Electrolyte a Novel Material for Electrochemical Devices: A Review
Authors: Singh Palvinder , Sachdeva Amit , Bhargava Cherry 
Published: September 2022

Abstract
Polymer Electrolyte is novel material as renewal energy sources are widely used in the industries. Electrolyte is the main parts of storing/conversion devices. In this review article polymer electrolyte novel material are discussed. In this report various polymer advantage, application, availability, categories of polymer, various approaches, and sample preparation techniques are also described. Polymer electrolyte also used in batteries, fuel cells, supercapacitors, Dye-sensitizes solar cell and energy storing/conversion devices. It is observed that polymer electrolyte is better awareness to the researchers and readers.
Understanding and Visualization of Different Feature Extraction Processes in Glaucoma Detection
Authors: Krishna Nanditha , Nagamani K 
Published: September 2022

Abstract
In the recent years the usage of mobile phone is increased and it is the major reason for cause of vision loss in several people. The continuous usage increases pressure inside optic nerve head and it leads to glaucoma disease. Also, there are lot of other reasons which leads to the cause of glaucoma. The purpose of this paper is to determine the importance of feature extraction process in glaucoma detection and implementation of different techniques for extracting convenient features for training machine learning model using pre-processed OCT (Optical Coherence Tomography) images. The two major feature extraction techniques narrated in this paper are convolutional neural network (CNN) model-based feature extraction and image processing model-based feature extraction. A performance analysis was conducted to find best feature extraction technique and both techniques performed well.
A Low Cost all Optical Photonic Technique Based on Brillouin Scattering for mm-Wave Generation
Authors: Bansal Mohit , Sindhwani Manoj 
Published: September 2022

Abstract
Generation of millimeter wave (mm-wave) in radio over fiber (ROF) systems is suffered from nonlinearity effects in optical fiber communication. In order to mitigate the degrading effects, a low cost all optical photonic method for the generation of mm-wave is proposed in this work. Therefore, work is accentuated on the enhanced frequency shift based on stimulated Brillouin scattering (SBS) by utilizing only one pump source. Effect of length of optical fiber, launched power and photo detector quantum efficiency is investigated over proposed architecture in order to observe power fading effects. Photonically stable, mm-wave is realized productively in the cost effective way using SBS incorporating different frequencies from 20 GHz-80 GHz. Results reveals that USB (upper sidebands) and LSB (lower sidebands) generated with demonstrated system have high power and good SNR. This makes system appropriate for radio over fiber system.
Estimation of Channel for Millimeter-Wave Hybrid Massive MIMO Systems using Orthogonal Matching Pursuit (OMP)
Authors: Shailender  , Khera Shelej , Singh Sajjan , Jyoti  
Published: September 2022

Abstract
In a millimeter-wave (mm-Wave) large MIMO system, hybrid precoding is a critical component for lowering radio-frequency hardware costs as compared to the traditional full-digital precoding strategy. Knowledge of channels is required for hybrid precoding. Though, estimation of the channel is problematic for the mm-Wave system because of the usage of a massive array of antenna and hybrid architecture with analog precoding. Due to the extremely directed nature of wireless propagation, wireless channels have spatial sparsity. In this paper, we exploit this spatial sparsity nature of wireless channels to develop orthogonal matching pursuit technique-based estimation of channels for hybrid millimeter-wave (mm-Wave) wireless systems. Genie (Ideal) channel estimation is also performed in which we presume that actual angle of departures (AoD) and angle of arrivals (AoA) are known to us. Finally, the simulation results reveal that suggested OMP algorithm-based channel estimation has a significant advantage over conventional approaches like least-squares channel estimation.