bluuebunny/crossref_metadata_2025_split huggingface dataset:
Diversity oriented clicking delivers β-substituted alkenyl sulfonyl fluorides as covalent human neutrophil elastase inhibitors
Authors: Cheng Yunfei , Li Gencheng , Smedley Christopher J. , Giel Marie-Claire , Kitamura Seiya , Woehl Jordan L. , Bianco Giulia , Forli Stefano , Homer Joshua A. , Cappiello John R. , Wolan Dennis W. , Moses John E. , Sharpless K. Barry 
Published: September 2022

Diversity Oriented Clicking (DOC) is a discovery method geared toward the rapid synthesis of functional libraries. It combines the best attributes of both classical and modern click chemistries. DOC strategies center upon the chemical diversification of core “SuFExable” hubs—exemplified by 2-Substituted-Alkynyl-1-Sulfonyl Fluorides (SASFs)—enabling the modular assembly of compounds through multiple reaction pathways. We report here a range of stereoselective Michael-type addition pathways from SASF hubs including reactions with secondary amines, carboxylates, 1
H
-1,2,3-triazole, and halides. These high yielding conjugate addition pathways deliver unprecedented β-substituted alkenyl sulfonyl fluorides as single isomers with minimal purification, greatly enriching the repertoire of DOC and holding true to the fundamentals of modular click chemistry. Further, we demonstrate the potential for biological function – a key objective of click chemistry – of this family of SASF-derived molecules as covalent inhibitors of human neutrophil elastase.
Natural band alignment of BAlN and BGaN alloys
Authors: Ota Yuichi , Imura Masataka , Banal Ryan G , Koide Yasuo 
Published: September 2022

Abstract
The natural band alignment of BAlN and BGaN alloys was investigated using the atomic solid-state energy scale approach. The band edge positions relative to the vacuum level were determined for BAlN and BGaN alloys, and the band offset values for each heterostructure were estimated. The results suggest that the natural band alignment of BAlN and BGaN alloys behaves according to the common anion rule. Further, the Schottky barrier height (SBH) was calculated based on the results of band alignment for BAlN and BGaN alloys. The predicted SBH values are expected to be an important guideline for boron nitride and its related alloy device design.
Enhanced production of hydroxyl radicals in plasma-treated water via a negative DC bias coupling
Authors: Lee Seungjun , Lee Jimo , Nam Woojin , Yun Gunsu 
Published: September 2022

Abstract
Hydroxyl radical (OH•) plays an important role in advanced oxidation processes (AOPs), which are employed to decompose organic pollutants in wastewater treatment. OH• is predominantly produced in AOPs for wastewater treatment via ultraviolet photolysis of hydrogen peroxide (H2O2) or ozone, which is a costly and difficult process. This paper introduces an enhanced OH• production method based on microwave-driven atmospheric pressure plasma with negatively biased water. Fluorescence analysis using terephthalic acid and 2-hydroxyterephthalic acid showed that the OH• concentration in a DC coupled plasma-treated water (PTW) can be increased by 1–2 orders of magnitude compared to the case with microwave plasma only. In addition, we found that there exists an optimal concentration of H2O2 in PTW for the ideal production of OH•. As a test case of AOPs, an Fe(III)-ethylenediaminetetraacetic acid solution containing H2O2 was treated with a DC coupled plasma for 10 min, and more than 80% decomposition was recorded.
Nuclear DFT analysis of electromagnetic moments in odd near doubly magic nuclei
Authors: Sassarini P L , Dobaczewski J , Bonnard J , Ruiz R F Garcia 
Published: September 2022

Abstract
We use the nuclear density functional theory to determine nuclear electric quadrupole and magnetic dipole moments in all one-particle and one-hole neighbours of eight doubly magic nuclei. We align angular momenta along the intrinsic axial-symmetry axis with broken time-reversal symmetry, which allows us to explore fully the self-consistent charge, spin, and current polarisation. Spectroscopic moments are determined for symmetry-restored wave functions and compared with available experimental data. We find that the obtained polarisations do not call for using quadrupole- or dipole-moment operators with effective charges or effective g-factors.
An improved two-stream compression convolution network for rolling bearing fault diagnosis
Authors: Jin Hailong , Ma Wuxu , Meng Zong , Sun Dengyun , Cao Wei , Fan Fengjie 
Published: September 2022

Abstract
The timely and accurate fault diagnosis of rolling bearings plays a vital role in ensuring the safe and reliable operation of many complex mechanical systems. However, most of the existing rolling bearing fault diagnosis models have complex structures, need a large number of samples, and cannot fully use the information contained in the signal. Based on these problems, an intelligent method for detecting and identifying rolling bearing faults is proposed based on an improved two-stream compression convolution network. The proposed method has a compact structure and powerful feature extraction capability, which consists of two modules. One adopts depthwise separable convolution and squeeze and excitation network, named DSCSE, which can fully extract the spatial features and greatly reduce the number of parameters. The other utilizes a one-dimensional convolutional neural network and spatial dropout mechanism, named 1DCNNSD, which can efficiently extract the temporal features and reduce model complexity. Meanwhile, to reduce the loss of information contained in the signal when the linear rectification unit is under negative input, the improved ReLU is designed. Numerous experiments demonstrate that the novel approach has higher accuracy, better generalization performance, and robustness than other methods under small samples.
Kinetic theory of particle-in-cell simulation plasma and the ensemble averaging technique
Authors: Touati Michaël , Codur Romain , Tsung Frank , Decyk Viktor K , Mori Warren B , Silva Luis O 
Published: September 2022

Abstract
We derive the kinetic theory of fluctuations in physically and numerically stable particle-in-cell (PIC) simulations of electrostatic plasmas. The starting point is the single-time correlation at the start of the simulation between the statistical fluctuations of the weighted densities of macroparticle centers in the plasma particle phase-space. The fluctuations are associated with different initial conditions, typically due to the random initial conditions (in velocity space) of the macroparticles/simulation plasma, assigned according to their initial distribution of probability. The single-time correlations at all time steps and in each spatial grid cell are then determined from the Laplace–Fourier transforms of the discretized Klimontovich-like equation for the macroparticles and Maxwell’s equations for the fields, as computed by modern PIC codes. We recover the expressions for the electrostatic field and the plasma particle density fluctuation autocorrelation spectra as well as the kinetic equations describing the average evolution of PIC-simulated plasma particles, first derived by Langdon (1970b Proc. 4th Conf. Numerical Simulation of Plasmas) using a test macroparticle approach perturbing a discretized Vlasovian plasma and then averaging the obtained physical quantity over the initial macroparticle velocity distribution. We generalize and extend these results to the modern algorithms in PIC codes using arbitrary macroparticle weights. Analytical estimates of statistical fluctuation amplitudes are derived as a function of the plasma simulation parameters, using the central limit theorem in the limit of a large number of macroparticles per cell. The theory is then used to analyze the ensemble averaging technique of PIC simulations where statistical averages are performed over ensembles of PIC simulations, modeling the same plasma physics problem but using different statistical realizations of the initial distribution functions of the macroparticles. This method is illustrated by linear Landau damping uncovering (from noise, which is usually considered numerical) the physical fluctuations driven by a single small amplitude electrostatic wave perturbing a PIC simulation plasma in equilibrium.
Study of anisotropy of convective optical underwater turbulence and the effect of the mean water temperature in the presence of a varying temperature gradient on it
Authors: Mohammadi Razi Ebrahim , Shokoohi Reza , Rasouli Saifollah 
Published: September 2022

Abstract
In this paper, the anisotropy of optical convective underwater turbulence is investigated in terms of the variance of angle of arrival (AOA) fluctuations of a narrow laser beam propagating through it in different sections of the medium. The collimated laser beam with a wavelength 532 nm and a diameter 1 cm, which passes through a convective underwater turbulence. The turbulence is generated in a water tank with dimensions of 20 cm × 36 cm × 20 cm, which is installed on a flat surface electrical heater. During the experiments, the mean water temperature (MWT) can be changed from room temperature to 34 ∘C by increasing the heater temperature. The use of the heater also generates a temperature gradient in the medium. The laser beam propagates along a horizontal path with a length of 20 cm inside the tank at different altitudes from the heater source, as well as at different distances from one of the side walls of the turbulent medium. After passing the laser beam through the turbulent medium, the fluctuations of the AOA components in the vertical and horizontal directions are measured. From the time series of the measured AOA fluctuations, their variances are determined. The anisotropy of the medium is investigated by comparing the variance of AOA components measured in the vertical and horizontal directions. We show that the variances of both of vertical and horizontal components of the AOA fluctuations are increased with the MWT, and they are saturated at higher MWTs. In addition, different anisotropic behaviors are observed for the variances of the measured AOA fluctuations at the vicinity of the lateral wall and upper surface of the water. At the vicinity of the lateral wall the variances of the AOA fluctuations in the horizontal component are larger, but at the vicinity of the upper surface the variances of the AOA fluctuations in the vertical component are dominant. This behavior may be caused by the change of the convection motion direction in the turbulent fluid.
Evolution of Galaxy Types and H i Gas in Hickson Compact Groups
Authors: Liu Yao , Zhu Ming 
Published: September 2022

Abstract
Compact groups have high galaxy densities and low velocity dispersions, and their group members have experienced numerous and frequent interactions during their lifetimes. They provide a unique environment to study the evolution of galaxies. We examined the galaxies types and H i contents in groups to make a study on the galaxy evolution in compact groups. We used the group crossing time as an age indicator for galaxy groups. Our sample is derived from the Hickson Compact Group catalog. We obtained group morphology data from the Hyper-Leda database and the IR classification based on Wide-Field Infrared Survey Explorer fluxes from Zucker et al. By cross-matching the latest released ALFALFA 100% H i source catalog with supplement by data found in literature, we obtained 40 galaxy groups with H i data available. We confirmed that the weak correlation between H i mass fraction and group crossing time found by Ai & Zhu in SDSS groups also exists in compact groups. We also found that the group spiral galaxy fraction is correlated with the group crossing time, but the actively star-forming galaxy fraction is not correlated with the group crossing time. These results seem to fit with the hypothesis that the sequential acquisition of neighbors from surrounding larger-scale structures has affected the morphology transition and star formation efficiency in compact groups.
Comparison of Power Efficient Inverter Circuit using adiabatic technique
Authors: Goel Mohit Kumar , Bharti Supriya , Kumar Parveen , Dandotiya Suman , Pal Abhishek , Tripathi Divyank 
Published: September 2022

Abstract
The power decadence in conventional CMOS (Complementary Metal oxide Semiconductor) circuit can be diminished by utilizing adiabatic method. Working of Adiabatic logic depends on switching activities, which diminishes the power by giving energy dissipated as heat back to supply. Adiabatic word has come from thermodynamic framework which says that no heat transfer take place from framework to climate as well as the other way around. Adiabatic logic is well known as energy recovery logic because its main objective is to reuse energy. It reuses the energy back to the power supply along the lines diminishing the power dissipation. Adiabatic procedures depend on adiabatic logic guideline. Anu Priya has propose the technique in 2014 [3], of adiabatic procedure where energy dissipation in PMOS organization can be limited and some of energy dissipated at load capacitance can be reused rather than dispersed as heat. Yet, the adiabatic method is exceptionally reliant upon parameter variation. Expecting completely adiabatic activity from a circuit is practically not possible as it is an ideal condition, also adiabatic technology is highly dependent on parameter variations so it’s quite difficult to achieve and ideal adiabatic circuit. It could be just accomplished with extremely sluggish exchanging speed. In examination, three logic families, ECRL (Efficient Charge Recovery Logic), PFAL (Positive Feedback Adiabatic Logic) and CPAL (Complementary Pass Transistor Adiabatic Logic) are contrasted and conventional CMOS logic for inverter circuit. MICROWIND technology is used while investigating different adiabatic circuits; energy utilization is broke down by variety of parameter. Result shows that adiabatic strategy is better decision in case of underpowered application in explicit frequency range.
High Performance Mixed Logic Decoders using MOS like GNRFET in 22nm Technology
Authors: Arora Sneha , Tripathi Suman Lata 
Published: September 2022

Abstract
Graphene nano ribbon field effect transistor is an emerging field of research in VLSI technology beyond 32nm. VLSI main motive is to reduce power consumption and other parameters such as delay, PDP (power delay product) to improve the efficiency. This article discusses the requirement for high-performance applications that use little power. However, employing low-power devices for high-rank applications such as microprocessors, digital signal processors, and static random-access memory (SRAM) is very challenging. In the field of memory design and logical circuit design, it is well recognised that the Decoder plays a crucial role. As part of the planned work in 22nm technology, a technique has been developed for evaluating the parameters Power delay product, Energy delay product, Power consumption, and Delay on 14T and 15T based employing 2 to 4 decoders based on MOSFET and GNRFET. So, the final proposed circuit is obtained by application of decoders with the use of GNRFET while improving the performance parameters.
Influence of fabrication parameters and optimization of supercapacitor – A simulation analysis
Authors: Yaquin Haziqul , Raam Dheep G 
Published: September 2022

Abstract
To develop comparative understanding on recent model of supercapacitor for various parameter values. The different parameters addressed here are performance variables of supercapacitor. Greenhouse gas emission mitigation, waste minimization and green technologies are need of hour. Conclusively environment protection is essential now for sustainability of life. This paper focuses on how effectively simulation software called MATLAB-Simulink be used to develop optimized model of supercapacitor before fabricating the real device.
Wireless sensor networks for forest fire monitoring: Issues and Challenges
Authors: Salaria Anshika , Singh Amandeep , Sharma Kamal Kumar 
Published: September 2022

Abstract
Forest fires have recently been the most critical issue faced by the world. The huge environmental, economic, and societal damages caused by wildfires are hindrances to social development. The increasing figures of such instances since the last few years make it the need of the hour to start considering it on priority and take appropriate actions. For this, intense knowledge is required about the nature of forest fires, their causes and appropriate technology to be used. Wireless sensor networks have always been a preferable technology in such kind of disaster management and environmental monitoring scenarios. However, there are yet some prominent issues that affect the overall performance of wireless sensor networks, especially in harsh terrains like forests. In this paper, information has been provided about the causes, damages and aftereffects of forest fires. Moreover, a study has been conducted on various articles highlighting the issues and challenges being faced in wireless sensor networks. The paper further provides a simple and easily understandable analysis highlighting the types and priority of challenges. This would benefit the researchers in identifying the current research gaps in the field of wireless sensor networks, especially in applications like forest fire monitoring or environmental monitoring and disaster management.
Charbonnier-Marchaud Based Fractional Variational Model for Motion Estimation in Multispectral Vision System
Authors: Kumar Pushpendra , Khan Muzammil 
Published: September 2022

Abstract
As we are aware that motion estimation is an active and challenging area of vision system, which leads to the applications of computer vision. In general, motion detection and tracking in the image sequence (video) is carried out based on optical flow. In the recent-past, researchers have made a significant contribution to the estimation of optical flow through integer order-based variational models, but these are limited to integer order differentiation. In this paper, a nonlinear modeling of fractional order variational model in optical flow estimation is introduced using the Charbonnier norm, which can be scaled to integer order L
1-norm. In particular, the variational functional is formulated by the inclusion of a non-quadratic penalty term, regularization term and the Marchaud’s fractional derivative. This non-quadratic penalty provides effective robustness against outliers, whereas the Marchaud’s fractional derivative possesses a non-local character, and therefore is capable to deal with discontinuous information about texture and edges, and yields a dense flow field. The numerical discretization of the Marchaud’s fractional derivative is employed with the help of Grünwald–Letnikov fractional derivative. The resulting nonlinear system is converted into a linear system and solved by an efficient numerical technique. Several experiments are performed over a spectrum of datasets. The robustness and accuracy of the proposed model are shown under different amounts of noise and through detailed comparisons with the recently published works.
An Approach to Fabric Defect Detection using Statistical Methods for Feature Extraction
Authors: Patil Girish , Deshmukh S. M. 
Published: September 2022

Abstract
Quality control in any commodity at every stage of production not only is desired but its reproduction day in and day out is essential in this fast changing world especially when we see that shopping from a digital screen is the new trend in this era of pandemic. Quality check, control and inspection demands manual checking where in the monotonous work can make a human negligible towards work and lead to reduction in quality control. The world demands replacement of such laborious work which can only be promised by machinery custom tailored from the needs of providing accuracy, time reduction in quality checks as well as production and most importantly reduction in labour cost when commodity manufacturing is concerned. One such commodity that we cover in this paper is the textile industry where in automated fabric defect detection is harnessed as the research trend across the world with the help of image processing combined with machine learning algorithms is concerned. This area of research is challenging as the algorithm needs to cover robustness, efficiency and particularly the variety of classifiable defects in terms of surety and complexity. Out of the various techniques utilised for fabric defect detection we have utilised a threshold based image processing technique that can provide an automated stepping stone for atomization in the fabric defect detection for quality control.
Bidirectional Passive Optical Network Employing Different Line codings/Modulation Formats in Wavelength Reused RSOA Based Symmetrical 10 Gbps
Authors: Ruchika  
Published: September 2022

Abstract
Passive optical networks (PONs) with the integration of multiple channels are the high capacity systems to cater the large number of channels in order to fulfill demands of internet applications. To realize a crosstalk suppressed and cost effective system, an integrated multi channel PON for mitigation of the crosstalk between upstream and downstream channels using different pulse shapes such as Return to zero (RZ), non RZ (NRZ), compressed spectrum RZ (CSRZ), Differential phase shift keying (DPSK) is proposed. Use of reflective semiconductor optical amplifier (RSOA) has been proposed for upstream modulation to make system cost efficient. 2-channel downstream and 2-channel upstream wavelengths are used to exhibits total symmetrical data rate of 10 Gbps. Results revealed that proposed system can support 10 Gbps data rate up to 20 km
Intelligent Reflecting Surface Aided MIMO - A Review
Authors: Srivastava Praveen , Tripathi Nishant , Srivastava Vikas , Pnadey Utkarsh 
Published: September 2022

Abstract
Intelligent Reflecting Surface (IRS) is a transformative and innovative technique for enhancing the energy efficiency of modern day communication for 5G and beyond networks. Multiple input multiple output (MIMO) is widely used technology as it enhances the energy and spectral efficiency of network. IRS in combination with MIMO is widely used to reduce the non-Line of sight communication losses and also to increase the efficiency. IRS is a tool which changes the phase of the incoming signal by transforming it to a discrete phase and retransmits it towards user. This paper present a deep insight to IRS aided MIMO communication network technology and latest work done in this area. A comparative analysis of works of different authors is represented in a tabular form so as to have a better insight into this area.
Optimization of Cell-Free Massive MIMO System
Authors: Sharma Manmohan , Verma Sunny , Verma Shekhar 
Published: September 2022

Abstract
As an innovative implementation, Cell-Free Massive Multiple Input Multiple Output (MIMO) has appeared in typical Cellular Massive MIMO Networks. This protocol doesn’t recognize cells, as shown by its name, even though a significant number of APs operate on the same frequency/time resources. Connection from multiple distributed access points through joint signal processing is called Cell-Free Massive MIMO. The Cell-Free Massive MIMO System, a contrast between Cell-Free Massive MIMO Systems and Distributed Massive MIMO, the prime focus in this thesis is on Cell-free Massive MIMO and, along with this discussion, on Cell-free Massive MIMO signal processing, Channel Estimation, Uplink Signal Detection, Cumulative Distribution, Spectral Efficiency & Ubiquitous Cell-Free Massive MIMO Model. Ubiquitous Cell-free Massive MIMO contributes to a Massive MIMO system, a distributed system that implements consistent user-centre distribution to solve that constraint of mobile phone interferences as well as to introduce macro-diversity. We investigated the Cell Radius at different locations in CDF with Spectral Efficiency [bits/s/hertz]. Cell-Free Massive MIMO is an evidence-based preventive of massive MIMOs with distributed high percentage APs that serve even lower margins. The cell-free model is not segregated into cells and any individual is concurrently represented by every Access point.