bluuebunny/crossref_metadata_2025_split huggingface dataset:
Slow Slip Events in the Kanto and Tokai Regions of Central Japan Detected Using Global Navigation Satellite System Data During 1994–2020
Authors: Nishimura Takuya 
Published: December 2020

AbstractSlow slip events (SSEs) along subduction zones play an important role in accommodating relative plate motion. SSEs interplay with large megathrust earthquakes and other slow earthquakes, including low frequency and very low frequency earthquakes. The Kanto and Tokai regions of central Japan host frequent slow and large earthquakes, with significant differences in slip behavior along the subduction zones in the Suruga Trough, Sagami Trough, and Japan Trench. In this study, we conducted a systematic search to estimate the fault models and durations of short‐term SSEs using continuous Global Navigation Satellite System data collected from 1994 to 2020. We detected 176 potential SSEs with moment magnitudes of 5.3–7.0 and durations of 0–80 days from the time series. Along the Sagami Trough, two shallow regions at a depth of 10–20 km host Mw ≥ 6.5 SSEs off of the Boso Peninsula and accommodate most of the relative plate motion aseismically. Some SSEs also occur on the deep plate interface down to ∼50 km without tectonic tremors. Along the Japan Trench, the cumulative slip of the SSEs exhibits a bi‐modal depth distribution to avoid the large slip areas of past megathrust earthquakes at 30–40 km depth. The shallow SSEs are in the same depth range (10–30 km) as tectonic tremors, but are spatially separate from tremors along the trench. The detected SSEs have limited temporal correlations with other slow earthquakes and earthquake swarms, which suggests that many factors control the genesis of slow and regular earthquakes.
Scaling Seismic Fault Thickness From the Laboratory to the Field
Authors: Ferrand Thomas P. , Nielsen Stefan , Labrousse Loïc , Schubnel Alexandre 
Published: December 2020

AbstractPseudotachylytes originate from the solidification of frictional melt, which transiently forms and lubricates the fault plane during an earthquake. Here, we observe how the pseudotachylyte thickness a scales with the relative displacement D both at the laboratory and field scales, for measured slip varying from microns to meters, over 6 orders of magnitude. Considering all the data jointly, a bend appears in the scaling relationship when slip and thickness reach ∼1 mm and 100 µm, respectively, i.e., MW > 1. This bend can be attributed to the melt thickness reaching a steady‐state value due to melting dynamics under shear heating, as is suggested by the solution of a Stefan problem with a migrating boundary. Each increment of fault is heating up due to fast shearing near the rupture tip and starting cooling by thermal diffusion upon rupture. The building and sustainability of a connected melt layer depend on this energy balance. For plurimillimetric thicknesses (a > 1 mm), melt thickness growth reflects in first approximation the rate of shear heating which appears to decay in D−1/2 to D−1, likely due to melt lubrication controlled by melt + solid suspension viscosity and mobility. The pseudotachylyte thickness scales with moment M0 and magnitude MW; therefore, thickness alone may be used to estimate magnitude on fossil faults in the field in the absence of displacement markers within a reasonable error margin.
Rapid Contraction of the Radius of Maximum Tangential Wind and Rapid Intensification of a Tropical Cyclone
Authors: Wu Qiaoyan , Ruan Zhenxin 
Published: December 2020

AbstractDuring the intensification of a tropical cyclone (TC), the radius of maximum tangential wind (RMW) often contracts due to the spin‐up of tangential wind being much faster inside the RMW than at the RMW itself. However, rapid RMW contractions prior to rapid intensification (RI) of TCs are observed. Statistical analysis of best‐track data for the North Atlantic between 2000 and 2017 indicates that rapid RMW contraction (≥20 nmi within 24 h) does not necessarily cause RI (≥30 kt within 24 h) of a TC. An efficient TC RI is generally seen if the RMW contracts to ≤30 nmi. The change (contraction or expansion) of the RMW is prevalent for weak storms, and RMW contraction is found to be at its most rapid for TC initial intensities ≤60 kt. Rapid RMW contraction and simultaneous RI generally occurs when the initial RMW is >30 nmi. Convective heating associated with very deep convective clouds with infrared brightness temperatures <208 K appearing toward the storm center is important for RMW contraction and sufficient amounts of the convective heating are important for intensification. Less convective heating is required to have the same intensification rate for a storm with an initially smaller RMW. A storm is more likely to experience RI with relatively less convective heating after the RMW contracts to a smaller size. This study demonstrates the role of convective heating on RMW contraction and storm spin‐up through different processes in the early stages of a TC.
Upscaling Net Ecosystem Exchange Over Heterogeneous Landscapes With Machine Learning
Authors: Reitz O. , Graf A. , Schmidt M. , Ketzler G. , Leuchner M. 
Published: December 2020

AbstractThis paper discusses different feature selection methods and CO2 flux data sets with a varying quality‐quantity balance for the application of a Random Forest model to predict daily CO2 fluxes at 250 m spatial resolution for the Rur catchment area in western Germany between 2010 and 2018. Measurements from eddy covariance stations of different ecosystem types, remotely sensed vegetation data from MODIS, and COSMO‐REA6 reanalysis data were used to train the model and predictions were validated by a spatial and temporal validation scheme. Results show the capabilities of a backwards feature elimination to remove irrelevant variables and an importance of high‐quality‐low‐quantity flux data set to improve predictions. However, results also show that spatial prediction is more difficult than temporal prediction by reflecting the mean value accurately though underestimating the variance of CO2 fluxes. Vegetated parts of the catchment acted as a CO2 sink during the investigation period, net capturing about 237 g C m−2 y−1. Croplands, coniferous forests, deciduous forests and grasslands were all sinks on average. The highest uptake was predicted to occur in late spring and early summer, while the catchment was a CO2 source in fall and winter. In conclusion, the Random Forest model predicted a narrower distribution of CO2 fluxes, though our methodological improvements look promising in order to achieve high‐resolution net ecosystem exchange data sets at the regional scale.
Using Turbulence to Identify Preferential Areas for Grass Carp (Ctenopharyngodon idella) Larvae in Streams: A Laboratory Study
Authors: Prada Andres F. , George Amy E. , Stahlschmidt Benjamin H. , Jackson P. Ryan , Chapman Duane C. , Tinoco Rafael O. 
Published: December 2020

AbstractIn this experimental series, we studied the swimming capabilities and response of grass carp (Ctenopharyngodon idella) larvae to flow turbulence in a laboratory flume. We compared three different experimental configurations, representing in‐stream obstructions commonly found in natural streams (e.g., a gravel bump, a single vertical cylinder, and patches of submerged rigid vegetation). Grass carp larvae (postgas bladder emergence) were introduced to each experimental configuration and subjected to a variety of hydrodynamic forces of different magnitudes and scales. We varied the flow velocities and water depths and found ranges of turbulent kinetic energy and Reynolds stresses that triggered a response in larval trajectories, identified by measured horizontal and vertical swimming speeds for each flow condition. Larvae apparently actively avoided areas with increased levels of turbulence by swimming away, moving faster in short bursts, and expending more energy. In addition to the magnitude of turbulent kinetic energy, the length scale and time scale of turbulent eddies also influenced the larvae response. These findings support the development of new strategies for controlling the spread of grass carp larvae in rivers, as well as the development of numerical tools incorporating active swimming capabilities to predict larval transport in streams.
Timescale and Effectiveness of Residual Saltwater Desalinization Behind Subsurface Dams in an Unconfined Aquifer
Authors: Zheng Tianyuan , Zheng Xilai , Chang Qinpeng , Zhan Hongbin , Walther Marc 
Published: December 2020

AbstractCountermeasures against saltwater intrusion (SWI) are critical to prevent coastal groundwater deterioration. Among different measures to prevent SWI, subsurface dams have shown to be an effective approach, but it is likely to produce residual saltwater behind the dam in a landward aquifer. This study investigated the influences of subsurface dam design and aquifer properties on the dynamic characteristics of residual saltwater in a field‐scale aquifer and for the first time revealed the desalinization mechanism of residual saltwater behind the dams from the point of mixing zone. It was found that the low‐concentration mixing zone (LCMZ) (for the area between 10% and 50% of seawater salinity) was a major channel for the saltwater to flow over the dam to the ocean boundary while the residual salt was continuously dispersed to the LCMZ from the high‐concentration mixing zone (HCMZ) (for the area between 50% and 90% of seawater salinity) under high‐concentration gradients. Moreover, we developed two formulas of the reduction rate of saltwater wedge length (RSWL*) and the removal rate of total residual salt mass (RTSM*) to evaluate the desalination effectiveness of high‐ and low‐concentration residual saltwater, respectively. The results showed that it took much longer time for a taller dam and a dam at a closer position to the sea boundary to desalinize the high‐concentration residual saltwater in the upstream aquifer, more than 50 years for the cases of dam height beyond 16 m. On the contrary, only a slightly shorter time was needed to remove the low‐concentration saltwater behind the dams with the decrease of the distance from the sea boundary. Aquifer properties including the hydraulic gradient, hydraulic conductivity, and dispersivity strongly altered the desalinization time of the residual saltwater. The dispersivity was found to be the most critical factor influencing the removal effectiveness of saltwater retained in the landward aquifer. Increase of dispersivity from 1 to 3 m can dramatically reduce the desalinization time from more than 30 to 4 years.
Evaluating Wind Fields for Use in Basin‐Scale Distributed Snow Models
Authors: Reynolds Dylan S. , Pflug Justin M. , Lundquist Jessica D. 
Published: December 2020

AbstractMountain winds are the driving force behind snow accumulation patterns in mountainous catchments, making accurate wind fields a prerequisite to accurate simulations of snow depth for ecological or water resource applications. In this study, we examine the effect that wind fields derived from different coarse data sets and downscaling schemes has on simulations of modeled snow depth at resolutions suitable for basin‐scale modeling (>50 m). Simulations are run over the Tuolumne River Basin, CA for the accumulation season of Water Year 2017 using the distributed snow model, SnowModel. We derived wind fields using observations from either sensor networks, the North American Land Data Assimilation System (12.5 km resolution), or High‐Resolution Rapid Refresh (HRRR, 3 km resolution) data, and downscaled using terrain‐based multipliers (MicroMet), a mass‐conserving flow model (WindNinja), or bilinear interpolation. Two wind fields derived from 3 km HRRR data and downscaled with respect to terrain produced snow depth maps that best matched observations of snow depth from airborne LiDAR. We find that modeling these wind fields at 100 and 50 m resolutions do not produce improvements in simulated snow depth when compared to wind fields modeled at a 150 m resolution due to their inability to represent wind dynamics at these scales. For input to distributed snow models at the basin‐scale, we recommend deriving wind fields from high resolution numerical weather prediction model output and downscaling with respect to terrain. Future studies should compare suspension schemes used in blowing snow models and investigate wind downscaling schemes of complexity between statistical and fluid dynamic models.
Dual branch convolutional neural network for copy move forgery detection
Authors: Goel Nidhi , Kaur Samarjeet , Bala Ruchika 
Published: December 2020

AbstractThe advent of digital era has seen a rise in the cases of illegal copying, distribution and forging of images. Even the most secure data channels sometimes suffer to validate the integrity of images. Forgery of multimedia data is devastating in various important applications like defence and satellite. Increased illegal tampering of images has paved way for research in the area of digital forensics. Copy move forgery is one of the various tampering techniques which is used for manipulating an image's content. A deep learning–based passive Copy Move Forgery Detection algorithm is proposed that uses a novel dual branch convolutional neural network to classify images as original and forged. The dual branch convolutional neural network extracts multi‐scale features by employing different kernel sizes in each branch. Fusion of extracted multi‐scale features is then performed to achieve a good accuracy, precision and recall scores. Experiment analysis on MICC F‐2000 dataset has been performed under two different kernel size combinations. Extensive result analysis and comparative analysis proves the efficacy of proposed architecture over existing architecture in terms of performance scores, computation time, and complexity.
Adaptive enhanced affine transformation for non‐rigid registration of visible and infrared images
Authors: Min Chaobo , Gu Yan , Li Yingjie , Yang Feng 
Published: December 2020

AbstractNon‐rigid registration, performing well in all‐weather and all‐day/night conditions, directly determine the reliability of visible (VIS) and infrared (IR) image fusion. On account of non‐planar scenes and differences between IR and VIS cameras, non‐linear transformation models are more helpful to non‐rigid image registration than the affine model. However, most of non‐linear models usually used on non‐rigid registration are constructed by control points at present. Aiming at the issue that the adaptiveness and generalization of the control‐point‐based models are limited, adaptive enhanced affine transformation (AEAT) is proposed for image registration, generalizing the affine model from linear to non‐linear case. Firstly, Gaussian weighted shape context, measuring the structural similarity between multimodal images, is designed to extract putative matches from edge maps of IR and VIS images. Secondly, to implement global image registration, the optimal parameters of the AEAT modal are estimated from putative matches by a strategy of subsection optimization. Experiment results show that this approach is robust in different registration tasks and outperforms several competitive methods on registration precision and speed.
Effect of Homeopathic Preparations on Lettuce, Parasitized or Not by Meloidogyne enterolobii
Authors: Ferreira Thais Moraes , Mangeiro Mariana Zandomênico , Almeida Alexandre Macedo , Souza Ricardo Moreira 
Published: December 2020

Abstract
Background There are relatively few scientific works on the use of homeopathy to manage plant pathogens, particularly nematodes. A handful of studies focused on Meloidogyne spp. parasitizing vegetables have brought contradictory results on nematode control and enhancement of plant tolerance to parasitism.
Objective Our goal was to assess the effect of Cina—a well-known anti-nematode ingredient—on Meloidogyne enterolobii parasitizing lettuce.
Methods Cina was applied daily on nematode-inoculated plants, from the seedling stage until harvest. We tested an evenly spaced range of Hahnemannian concentrations (c), which were applied though irrigation with a constant dose of the ingredient. Several absolute and relative controls were employed to allow the assessment of the effect of Cina on nematode reproduction and lettuce growth.
Results Cina affected growth of non-parasitized plants, both positively and negatively; this effect was modulated by the c applied and the thermal stress suffered by the plants in one of the assays. The effect of Cina on the growth of nematode-parasitized plants was neutral or negative. Cina reduced nematode reproduction by 25–36%.
Conclusion Based on the moderate negative effect of Cina on M. enterolobii reproduction, it seems this ingredient may be useful as a complementary strategy for Meloidogyne control. But Cina did not enhance the tolerance of lettuce to Meloidogyne spp.
Social Vulnerability among Foreign-Born Pregnant Women and Maternal Virologic Control of HIV
Authors: Premkumar Ashish , Yee Lynn M. , Benes Lia , Miller Emily S. 
Published: December 2020

Objective The aim of this study was to assess whether social vulnerability among foreign-born pregnant women living with HIV is associated with maternal viremia during pregnancy.
Study Design This retrospective cohort study included all foreign-born pregnant women living with HIV who received prenatal care in a multidisciplinary prenatal clinic between 2009 and 2018. A licensed clinical social worker evaluated all women and kept detailed clinical records on immigration status and social support. Social vulnerability was defined as both living in the United States for less than 5 years and reporting no family or friends for support. The primary outcome was evidence of viral non-suppression after achievement of initial suppression. Secondary outcomes were the proportion of women who required > 12 weeks after starting antiretroviral therapy to achieve viral suppression, median time to first viral suppression (in weeks) after initiation of antiretroviral therapy, and the proportion who missed ≥ 5 doses of antiretroviral therapy. Bivariable analyses were performed.
Results A total of 111 foreign-born women were eligible for analysis, of whom 25 (23%) were classified as socially vulnerable. Social and clinical characteristics of women diverged by social vulnerability categorization but no differences reached statistical significance. On bivariable analysis, socially-vulnerable women were at increased risk for needing > 12 weeks to achieve viral suppression (relative risk: 1.78, 95% confidence interval: 1.18–2.67), though there was no association with missing ≥ 5 doses of antiretroviral therapy or median time to viral suppression after initiation of antiretroviral therapy.
Conclusion Among foreign-born, pregnant women living with HIV, markers of virologic control during pregnancy were noted to be worse among socially-vulnerable women. Insofar as maternal viremia is the predominant driver of perinatal transmission, closer clinical surveillance and support may be indicated in this population.
Key Points
Data Processing and Management in IoT and Wireless Sensor Network
Authors: Sasirekha S.P. , Priya A. , Anita T. , Sherubha P. 
Published: December 2020

Abstract
The deployment of internet over larger scale may introduce huge challenges based on data processing. The enormous amount of IoT based data needs design-based solution for faster data processing and improving its extensibility and adaptability. Based on various IoT based data processing, servicing technologies may provide data-centric models for scalable services. This work concentrates on an extensive review towards the scalable realization and acquisition of data for process. This IoT based services are larger enough to be concentrated. This review gives an insight towards the data processing and management in IoT and sensor-based networking.
Arduino Based Authenticated Voting Machine (AVM) using RFID and Fingerprint for the Student Elections
Authors: Vinayachandra  , Poornima K Geetha , Rajeshwari M , Prasad K Krishna 
Published: December 2020

Abstract
The guiding principles of democracy are free elections. Through elections, people reaffirm their voice, their beliefs, and select someone whose ideas support them most. Voters will elect their representatives via elections. The purpose of the elections is not only to decide the outcome but also to give the winners credence, also for those voters who did not bother to vote for them. The need to hold free, equal, and secret elections is emphasized here. It involves the supervision of elections by free, accountable, impartial and autonomous electoral bodies. As the phrase is ‘today teens, tomorrow’s citizens,’ the student community needs the process of elections to be involved, trained, and acquainted with. Under this respect, the institutions of higher education hold elections in the form of general elections to the Office of the student councils. By this student will receive first-hand information about filing nomination, scrutiny of papers, withdrawing, canvassing, addressing, and most importantly voting. The use of technology in voting will make it easier, more effective, and less prone to breaches of security. Technology will boost and speed up the safety of all votes and make the counting and automated verification much more effective. The design of an advanced voting system is a difficult task as many main requirements have to be met. The secrecy of a poll should be maintained. No proof of which candidate gets particular voting shall be provided by the voting system. The authors implemented the Authenticated Voting Machine in the College elections in this paper to ease the process and improve transparency. The concept is still in its infancy and requires more research to keep it stable and theoretically strong. To ensure protection, the model uses radiofrequency and fingerprint recognition.
Future enhancements and propensities in forthcoming communication system – 5G Network Technology
Authors: Vikranth K. , Anvar Shathik J , Jeetha  , Prasad K. Krishna 
Published: December 2020

Abstract
Network technology and mobile technologies are two essential and booming technologies in today’s scenario that have emerged and quickly evaluated in terms of hardware, communication media, and architecture. Based on the communication system there are massive developments in underlying devices with hardware, software, and entire architecture. All we experienced with 2G, 3G, and 4G communication system, and in the future, we will going to experience next-generation communication system 5G. In underlying technology there have been many improvements and advances, mainly with data transfer speed and unlimited bandwidth that we have never experienced before. Not only is this technology limited to voice and data, but we also expect some IoT revolutions, a system for mobile communication, automated vehicles, industrial and manufacturing automation, human-machine interface, logistics and warehousing, etc. So this 5G technology gives the opportunity for researchers to perform research in related technologies. Here we analyzed the need, concept, service and features of fifth generation communication technologies in this paper. It was proposed the core technology incorporated with 5G and their architecture. Future trends and applications influenced by the 5G communication system were analysed.
Detecting Chronic Kidney Disease from Blood Samples using Neural Networks
Authors: Latheef Mohamed Ghaisan , Logeswaran Rajasvaran , Mohtar Nurul Haniza 
Published: December 2020

Abstract
This paper proposes an artificial neural network approach to automatically detecting Chronic Kidney Disease through fluid samples taken from patients. The rationale for developing such a system is given, as well as possible benefits to the patients and medical industry. Similar systems proposed in the industry and for diagnosing chronic kidney disease through other approaches such as classification algorithms are explored. A dataset to train the neural network on is collected and features analysed, as well as methodology and tools to be used in the development of the neural network.