bluuebunny/crossref_metadata_2025_split huggingface dataset:
Non-linear photonic loop mirror based co-site interference canceller
Authors: Chandrasenan Archa , Zacharias Joseph 
Published: October 2022

Abstract
Full duplex-in band (FDIB) is a well-established solution for increasing the data rate and spreading the link range for future communication systems. FDIB systems need no additional bandwidth requirement. However, they are confronted with a major interference challenge on the same site, called co-site interference (CSI). Long-established co-site interference cancellation (CSIC) methods achieve a cancellation depth upto 35 dB, conversely it has space containments, manufacturing imperfections, induces noise penalties and limits isolation bandwidth. To overcome these problems, RF photonic CSIC methods have been developed, which have produced 30 dB wide-band interference suppression. They also increase bandwidth, have a flexible structure, minimize losses and prevent periodic power fading. But these systems have a problem of inherent DC drift, low maintenance of coherence, and low isolation at low transmission power. Thus, there is a high need for photonic CSIC designs of FDIB systems that operate over wider bandwidths and at higher transmission powers. Here, a newfangled CSIC system based on a non-linear photonic loop and frequency down-conversion is proposed. It shows excellent CSIC suppression of greater than 61 dB, for a single frequency signal of interest (SOI) with maximum RF power of 13 dBm. Without frequency down-conversion, the system maintains an average cancellation depth of 62.541 dB for single frequency SOI. After frequency down conversion, the system maintains an average cancellation depth of 61.208 dB for narrow band SOI. The system attains 18% error vector magnitude at −20 dB RF output power, which confirms the comprehensive quality of the system.
Development of a miniaturized, reconnectable, and implantable multichannel connector
Authors: Choi Gwang Jin , Yoo Hyun Ji , Cho YoonKyung , Shim Shinyong , Yun Seunghyeon , Sung Jaehoon , Lim Yoonseob , Jun Sang Beom , Kim Sung June 
Published: October 2022

Abstract

Objective. Connectors for implantable neural prosthetic systems provide several advantages such as simplification of surgery, safe replacement of implanted devices, and modular design of the implant systems. With the rapid advancement of technologies for neural implants, miniaturized multichannel implantable connectors are also required. In this study, we propose a reconnectable and area-efficient multichannel implantable connector. Approach. A female-to-female adapter was fabricated using the thermal-press bonding of micropatterned liquid crystal polymer films. A bump inside the adapter enabled a reliable electrical connection by increasing the contact pressure between the contact pads of the adapter and the inserted cable. After connection, the adapter is enclosed in a metal case sealed with silicone elastomer packing. With different sizes of the packings, leakage current tests were performed under accelerated conditions to determine the optimal design for long-term reliability. Repeated connection tests were performed to verify the durability and reconnectability of the fabricated connector. The connector was implanted in rats, and the leakage currents were monitored to evaluate the stability of the connector in vivo. Main results. The fabricated four- and eight-channel implantable connectors, assembled with the metal cases, had a diameter and length of 6 and 17 mm, respectively. Further, the contact resistances of the four- and eight-channel connectors were 53.2 and 75.2 mΩ, respectively. The electrical contact remained stable during repeated connection tests (50 times). The fabricated connectors with packings having 125%, 137%, and 150% volume ratios to the internal space of the metal case failed after 14, 88, and 14 d, respectively, in a 75 °C saline environment. In animal tests with rats, the connector maintained low leakage current levels for up to 92 d. Significance. An implantable and reconnectable multichannel connector was developed and evaluated. The feasibility of the proposed connector was evaluated in terms of electrical and mechanical characteristics as well as sealing performance. The proposed connector is expected to have potential applications in implantable neural prosthetic systems.
Hybrid mental tasks based human computer interface via integration of pronunciation and motor imagery
Authors: Tong Jigang , Wei Xiaoying , Dong Enzeng , Sun Zhe , Du Shengzhi , Duan Feng 
Published: October 2022

Abstract

Objective. Among the existing active brain–computer interfaces (BCI), the motor imagination (MI) is widely used. To operate the MI BCI effectively, subjects need to carry out trainings on corresponding imagining tasks. Here, we studied how to reduce the discomfort and fatigue of active BCI imaginary tasks and the inability to concentrate on them while improving the accuracy. Approach. This paper proposes a hybrid BCI composed of MI and pronunciation imagination (PI). The electroencephalogram signals of ten subjects are recognized by the adaptive Riemannian distance classification and the improved frequency selective filter-bank Common Spatial Pattern recognition. Main results. The results show that under the new paradigm with the combination of MI and PI, the recognition accuracy is higher than the MI alone. The highest recognition rate of the proposed hybrid system can reach more than 90%. Furthermore, through the subjects’ scoring results of the operation difficulty, it is concluded that the designed hybrid paradigm is more operable than the traditional BCI paradigm. Significance. The separable tasks in the active BCI are limited and the accuracy needs to be improved. The new hybrid paradigm proposed by us improves the accuracy and operability of the active BCI system, providing a new possibility for the research direction of the active BCI.
Fusion by beam ions in a low collisionality, high mirror ratio magnetic mirror
Authors: Egedal J. , Endrizzi D. , Forest C.B. , Fowler T.K. 
Published: October 2022

Abstract
The classical problem of neutral beam ions slowing down in a magnetic mirror geometry is revisited to provide predictive capability for the new Wisconsin HTS Axisymmetric Mirror under development at the University of Wisconsin. A Fokker–Planck model named fast beam ion solver (FBIS) is developed to include the spatial non-uniformity of a physical mirror geometry. The mathematical framework allows for efficient orbit averaging of the pitch-angle scattering operator, and permits a determination of the axial profile of the ambipolar potential confining the electrons. The numerical results from FBIS are consistent with earlier work, but further show how mirror-ratio and a near square magnetic well optimizes the fusion gain. The numerical results are also applied to inform the conceptual design of WHAM++, a low capital-cost breakeven-class magnetic mirror device.
Observation and analysis of lower-hybrid-current-drive density limit in EAST
Authors: Li M.H. , Baek S.G. , Wallace G.M. , Ding B.J. , Wu C.B. , Yan G.H. , Bonoli P.T. , Wang M. , Liu L. , Zhao L.M. , Wu Z.G. , Yang H. , Lin S.Y. , Zang Q. , Yan N. , Zhao H.L. , Huang J. , Zhai X.M. , Li X.X. , Zhang X.J. , Gong X.Z. 
Published: October 2022

Abstract
Lower hybrid current drive (LHCD) experiments with line-averaged density up to ∼5.1 × 1019 m−3 were performed in EAST L-mode plasmas. When the line-averaged density rises above a critical value, the hard x-ray (HXR) emission falls to the noise level, indicating that the LHCD density limit is encountered. The experimental results show that the LHCD density limit can be increased with higher wave source frequency (f
0) and higher magnetic field (B
t). Although a higher LHCD density limit is obtained by a higher magnetic field for both 2.45 GHz and 4.6 GHz waves, the results show a stronger dependence on the magnetic field for the 4.6 GHz case. Analysis suggests that, for normal operation with a relatively low magnetic field (1.6 T ⩽ B
t ⩽ 2.5 T) on EAST, the dominant mechanisms responsible for the LHCD density limit are different between the 2.45 GHz and 4.6 GHz waves. The wave accessibility plays a more significant role during 4.6 GHz LHCD experiments, while parasitic losses due to parametric decay instability (PDIs) dominate the accessibility issue in the 2.45 GHz case. Collisional loss in the scrape-off layer (SOL) may explain the 4.6 GHz result when combined with the accessibility limit at high density and low temperature.
Extension of the energetic particle transport kick model in TRANSP to multiple fast ion species
Authors: Podestà M. , Gorelenkova M. , Teplukhina A.A. , Bonofiglo P.J. , Dumont R. , Keeling D. , Poli F.M. , White R.B. , JET Contributors  
Published: October 2022

Abstract
Alfvénic instabilities (AEs) are well known to cause enhanced transport of energetic particles (EPs) in fusion devices. Most studies until now have focused on characterizing and understanding AE stability in single-species plasmas heated by neutral beams (NB), where deuterium is typically used as both main plasma species and NB fuel. As the fusion community moves toward fusion reactors that target burning plasma conditions, such as ITER, the single-species picture breaks down. Burning plasmas, which will use a mix of deuterium and tritium (DT) as main fuel, also feature the presence of several supra-thermal fusion products such as alpha particles, protons, helium isotopes and high-energy tritium ions. This work presents the extension of the EP transport kick model implemented in the TRANSP time-dependent tokamak transport code to study the combined effect of multiple EP species on AE stability and, in turn, the response of different EP species to plasma instabilities in terms of their redistribution and losses. Further validation of the enhanced model is planned based on experimental results expected from the JET DT campaign scheduled for 2021, in preparation for ITER plasmas and beyond.
TCAD simulation of radiation hard n-MCz and n-Fz Si microstrip detector for the HL-LHC
Authors: Kaur B. , Patyal S. , Saini N. , Chatterjee P. , Srivastava A.K. 
Published: October 2022

Abstract
A radiation hard Si detector is used in the new CMS tracker detector at HL-LHC. It has been observed that n-MCz and n-Fz Si as a material can be used for the Si micro strip detector. The detector design for this material should be simulated and optimized to get high CCE. In order to understand the charge collection behavior of the n-MCz/n-FzSi detector, it is required to simulate and compare the radiation damage effects in the mixed irradiated n-MCz Si and proton irradiated n-Fz Si micro strip detector equipped with metal overhang and multiple guard rings. In this paper, we have done analysis and optimization of the radiation hard n-MCz Si/n-Fz Si strip detector design for the HL-LHC experiment in order to get high CCE.
Role of Artificial Intelligence in improving structural performance: A Review
Authors: Shandilya Tanmay , Agrawal Vinay , Gupta Rajesh 
Published: October 2022

Abstract
Artificial Intelligence, or AI, encloses within itself, the various techniques and algorithms that facilitate the augmentation of human decision-making by adding computational infrastructure to it. It includes specific methodologies and programs that help make conclusive deductions based on the data available for it to work. The paper attempts to provide an introduction to the different types of AI tools along with their applicability. Furthermore, it attempts to define the role of AI in the enhancement of structural performance. Civil Engineering is a discipline that is highly dependent on the judgement of the Engineer-on-field. AI can assist this judgement by providing meaningful insights on the real world problems based on the data available from the site thereby improving the quality of the work and simultaneously serve as a guideline for novice engineers. This paper highlights the significance of AI in different domains of Civil Engineering and provides a broad picture of the future possibilities. It provides a review of the prominent works that have been carried out in the area and segregates the researches needing immediate attention. The areas of focus include structural performance parameters including prediction of structural properties, structural health monitoring and infrastructure-specific issues in buildings and bridges.
Life Cycle Cost Analysis of rooftop gardens using openLCA
Authors: Dhivya Barathi R , Vidjeapriya R 
Published: October 2022

Abstract
Most innovative and eco-friendly project alternatives are rejected due to higher initial costs. This problem arises due to the general cost analysis that considers only the initial costs. It can be solved using Life Cycle Cost Analysis (LCCA) approach because LCCA helps the decision makers to select the project alternative with more economic benefits by considering the costs incurred in it throughout the life cycle. In this paper, the life cycle cost analysis of the rooftop garden was carried out and compared with the conventional roof using openLCA software. The rooftop garden includes many environmental benefits such as the reduction of the urban heat island effect, reduction of noise pollution, improvement in quality of air, management of surface runoff and conservation of biodiversity. Still, the use of rooftop gardens is not common in the projects due to their higher initial costs. Thus, LCCA was carried out to evaluate its economic feasibility. A model was developed using openLCA software to carry out the analysis. The costs considered in the analysis include the initial costs, maintenance costs, renovation costs and energy costs. The cost data were collected for extensive rooftop gardens laid in commercial buildings in and around Chennai city. The results indicate that the initial cost of the rooftop garden was 5.2 times higher than that of the conventional roof but due to the prolonged life period and the energy savings of the rooftop garden, the life cycle cost was 5.25% lower than that of the conventional roof.
Optimum Orientation of Geofoam Inclusion in the Retaining Wall
Authors: Premanvitha P , Sravanam Sasanka Mouli 
Published: October 2022

Abstract
Expanded polystyrene (EPS) geofoam is one of the lightweight materials used in civil engineering applications. Present study deals with the application of geofoam in the retaining wall as a backfill. In this study, two-dimensional finite element software is used to simulate a retaining wall with geofoam. A wall of 6m height is considered. Lateral pressures and surface settlements are examined for various orientations of geofoam. Orientations include upper triangular, lower triangular, and rectangular patterns. The results are generalized for various wall heights. Placement of geofoam in rectangular pattern is found to lead the least lateral pressure.
Accident analysis and road safety audit: a case study on NH-76
Authors: Izharul Haque Md , Khan Amir Ali , Singh Gyanendra , Dass Sachin , Jaglan Saurabh 
Published: October 2022

Abstract
Road accidents in India are on the rise as the country’s vehicle population grows. As a result, a considerable number of lives and assets have been lost. The formal process for determining causal factors responsible for road accidents in new or improvement of existing road projects without any major modification in the design is known as a road safety audit. This study examines the traffic safety situation on NH-76 from Udaipur to Chittorgarh in the state of Rajasthan, India, intending to identify causal factors responsible for road accidents so that the real damage resulting from road collisions can be reduced to some extent in the future. For this study, a 93.5-kilometer span was chosen and accident data was obtained from the enforcement department via recorded accident FIRs from 2017 to 2019. The accident data was studied to determine the reasons, taking into account yearly, hourly, time-wise, day-wise variation, accident nature-wise, and other factors. Black spots were also identified in the study area and recommendations based on analysis were made to prevent traffic accidents and make the route safer for users. The purpose of this study is to uncover flaws, improve design characteristics, and improve road credibility.
A Study on Road Safety Audit and Black Spot Identification
Authors: Nuli Sadguna , Rohan Katkam , Joshnavi Chenreddy 
Published: October 2022

Abstract
Road Safety Audit (RSA) is a formal procedure for assessing accident potential and safety performance of new and existing roads. Road safety audit is an efficient, cost effective and proactive approach to improve road safety. It is proved that RSA has the potential to save lives. The RSA was originated in Great Britain and is well developed in countries like UK, USA, Australia, New Zealand, Denmark, Canada, Malaysia and Singapore. Presently, it is at varying stages of implementation in developing nations like India, South Africa, Thailand and Bangladesh. Therefore, road safety audit appears to be an ideal tool for improving road safety in India. In this study, a rural road stretching from Rallaguda bridge to Vardhaman College of Engineering in Hyderabad city is chosen for road safety audit. Safety assessment is done using iRAP application by collecting road side features, midblock details, intersection features, vulnerable road users’ facilities, speed and flow details. The secondary objective is to find out the Black Spot locations within Rajiv Gandhi International Airport (RGIA) police station jurisdiction of Hyderabad city. Accident prone areas are identified by estimating Weighted severity and accident severity indices with the help of historical accident data. Finally, major causes of accidents and measures to improve safety of the chosen road section are suggested.
Real-Time Traffic Prediction Using Neural Networks
Authors: Nuli Sadguna , Vikranth Nagula , Gupta Kothuri Avinash 
Published: October 2022

Abstract
Somewhat recently, the issue of traffic has become more extreme because of industrialization particularly in significant urban communities. A higher standard of living in cities is pushing people to utilise their own vehicles instead of public transportation. Thus, there is tremendous increase in traffic, which leads to a variety of other associated issues. In order to get from one place to another, one must spend more time travelling than they would have otherwise, which also raises the fuel consumption. The traffic data that is gathered by various detectors is highly dynamic and non-stationary. For example, the number of vehicles turning at an intersection cannot be stated with greater accuracy. Consequently, it is challenging to develop a mathematical model to determine green time. However, the introduction of Intelligent Transportation Systems (ITS) in modern times enables the detection of traffic events, communication, information processing, and user action. One of the most crucial criteria for this system to work successfully is the ability to precisely predict the pattern of the traffic stream. In order to predict future traffic flow, a system that uses artificial neural networks and real-time traffic data was proposed in this study. Neural networks have the ability to predict the future by learning from the past. Specifically, this study predict traffic volume in two levels such as short-term for every 15 minutes interval and mid-term for every one hour of a given day. These predictions help in dynamic traffic management applications like signal control, congestion management, and travel time predictions etc.
Flood Forecasting Using Artificial Neural Network
Authors: Mistry Shivangi , Parekh Falguni 
Published: October 2022

Abstract
The process of assessing the timing, amount, and period of flood events based on observed features of a river basin is known as flood forecasting. Floods cause lots of damage to properties and create a risk to human life. Flood forecasting is critical for developing appropriate flood risk management strategies, reducing flood hazards, evacuating people from flood-prone areas. The main objective of this study is to apply artificial neural networks for forecasting of river flow in the Deo River, located in Gujarat. Rainfall and discharge are the parameters considered for model development. The developed model is validated to test the accuracy of the model. Trained and validated models are evaluated using performance indices. Six alternative flood prediction models have been developed using ANN. These models are developed based on various training algorithms. A single layer feed forward back-propagation neural network with six different training algorithms (Scaled conjugate gradient, Levenberg Marquardt, Resilient back-propagation, Conjugate gradient, and Cascade forward back propagation, Bayesian regularization) was developed, with 70% of the data used for training and 30% for validation. The created models’ performance is assessed using statistical performance parameters. The best performance was obtained with an ANN model developed using the Cascade forward back-propagation training algorithm, which had a coefficient of correlation (r) of 0.83, a coefficient of determination (R2) of 0.70, and a root mean squared error (RMSE) of 5.58 for training and a coefficient of correlation (r) of 0.89, a coefficient of determination (R2) of 0.70, and a root mean squared error (RMSE) of 7.27 for validation. The forecast inflow is very close to the observed values. This study shows that ANN can be used to successfully predict floods, and the model developed can be used by flood control departments across the country for flood forecasting.
Coconut shell derived coal as low-cost adsorbent for the fluoride removal from drinking water
Authors: Bhamare Pratik , Bagul Tushar , More Ashok , Gadekar Mahesh 
Published: October 2022

Abstract
Fluoride in drinking water pose several health issues such as fluorosis, thyroid problems, neurological problems and fluoride poisoning. Amongst several approaches adsorption is one of a better low-cost technique. Present study focused on the use of granular coal made up of coconut shell as adsorbent for the fluoride removal from drinking water. The batch adsorption study conducted to study effect of fluoride concentration (2-10 mg/L), adsorbent dosage (2-10 g/L), pH (4-8), and contact time (0-120 min) on adsorption performance. Maximum adsorption of 1.37 mg/g was observed at pH of 5.9, adsorbent dose of 2 g/L, at 60 min of contact time. Furthermore, the data was fitted in Langmuir and Freundlich model and also modelled in the Artificial Neural Network (ANN). ANN shows a better modelling with coefficient of correlation about 98% and close to zero mean square error. The study indicates that coconut shell’s coal easy to prepare at rural locations and would be a low-cost adsorbent.