bluuebunny/crossref_metadata_2025_split huggingface dataset:
Rubus niveus (Mysore raspberry).
Authors: Pollard Kate 
Published: June 2021

Abstract

R. niveus is a highly invasive perennial shrub native to India, China and Southeast Asia. It was introduced around the world through the horticultural trade for its production of sweet tasting fruit and as an ornamental due to the striking red-purple colour of its stems. Nevertheless, cultivated crops were abandoned due to the formation of dense, spiny thickets and many R. niveus plants escaped from cultivation aided by the distribution of seed by birds. Outside of cultivation, R. niveus can outcompete native vegetation, decrease biodiversity and threaten rare endemic species. The success of many Rubus species is linked to the rapid growth of the roots and their ability to reproduce vegetatively. R. niveus has been described as the most invasive weed species on the Galápagos archipelago and declared a noxious weed in the state of Hawaii, USA (Starr et al., 2003).
Pueraria montana var. lobata (kudzu).
Authors: Pasiecznik Nick 
Published: June 2021

Abstract

P. montana, formerly known as P. lobata, is widely known in the USA as 'kudzu' is native to East Asia. However, it does not appear to be a significant problem anywhere except in south-eastern USA where it was extensively planted in the 1930s and 1940s for erosion control. Seed dispersal appears to be minor but vegetative growth in subtropical areas can be substantial, up to 18 m per growing season. It is a climbing vine and kills vegetation by completely smothering it, and it will also entirely cover telegraph poles and buildings if left to itself. Once introduced it is difficult to control, especially in forest and marginal habitats. There are three varieties, although only var. lobata is so far known to be invasive, in the USA.
Cissus verticillata (possum grape vine).
Authors: Rojas-Sandoval Julissa 
Published: June 2021

Abstract

Cissus verticillata is a large, climbing species cultivated as an ornamental and medicinal plant around the world. It is native to Mexico, Central America and the Caribbean. Once established, C. verticillata grows climbing over the top of the canopy and supporting itself by means of coiled tendrils, or scrambling over the ground. It is common to find this species engulfing entire trees. If the plant is cut, the remaining branches and stems can develop aerial roots that will find their way to the ground, regenerating new. C. verticillata is regarded as a weed in areas within and outside its native distribution range. It was reported in the Lower Rio Grande Valley in Texas in 2003 and may pose a potential weed problem in the citrus groves there and in Florida.
Reconstruction, analysis and interpretation of posterior probability distributions of PET images, using the posterior bootstrap
Authors: Filipović Marina , Dautremer Thomas , Comtat Claude , Stute Simon , Barat Éric 
Published: June 2021

Abstract
The uncertainty of reconstructed PET images remains difficult to assess and to interpret for the use in diagnostic and quantification tasks. Here we provide (1) an easy-to-use methodology for uncertainty assessment for almost any Bayesian model in PET reconstruction from single datasets and (2) a detailed analysis and interpretation of produced posterior image distributions. We apply a recent posterior bootstrap framework to the PET image reconstruction inverse problem and obtain simple parallelizable algorithms based on random weights and on existing maximum a posteriori (MAP) (posterior maximum) optimization-based algorithms. Posterior distributions are produced, analyzed and interpreted for several common Bayesian models. Their relationship with the distribution of the MAP image estimate over multiple dataset realizations is exposed. The coverage properties of posterior distributions are validated. More insight is obtained for the interpretation of posterior distributions in order to open the way for including uncertainty information into diagnostic and quantification tasks.
Sub-millimeter precise photon interaction position determination in large monolithic scintillators via convolutional neural network algorithms
Authors: Kawula M , Binder T M , Liprandi S , Viegas R , Parodi K , Thirolf P G 
Published: June 2021

Abstract
In this work, we present the development and application of a convolutional neural network (CNN)-based algorithm to precisely determine the interaction position of γ-quanta in large monolithic scintillators. Those are used as an absorber component of a Compton camera (CC) system under development for ion beam range verification via prompt-gamma imaging. We examined two scintillation crystals: LaBr3:Ce and CeBr3. Each crystal had dimensions of 50.8 mm × 50.8 mm × 30 mm and was coupled to a 64-fold segmented multi-anode photomultiplier tube (PMT) with an 8 × 8 pixel arrangement. We determined the spatial resolution for three photon energies of 662, 1.17 and 1.33 MeV obtained from 2D detector scans with tightly collimated 137Cs and 60Co photon sources. With the new algorithm we achieved a spatial resolution for the CeBr3 crystal below 1.11(8) mm and below 0.98(7) mm for the LaBr3:Ce detector for all investigated energies between 662 keV and 1.33 MeV. We thereby improved the performance by more than a factor of 2.5 compared to the previously used categorical average pattern algorithm, which is a variation of the well-established k-nearest neighbor algorithm. The trained CNN has a low memory footprint and enables the reconstruction of up to 104 events per second with only one GPU. Those improvements are crucial on the way to future clinical in vivo applicability of the CC for ion beam range verification.
Photo-emission signatures of coherence breakdown in Kondo alloys: dynamical mean-field theory approach
Authors: Poudel B , Lacroix C , Zwicknagl G , Burdin S 
Published: June 2021

Abstract
We study the Kondo alloy model on a square lattice using dynamical mean-field theory for Kondo substitution and disorder effects, together with static mean-field approximations. We computed and analyzed photoemission properties as a function of electronic filling n

c
, Kondo impurity concentration x, and strength of Kondo temperature T
K. We provide a complete description of the angle resolved photoemission spectroscopy (ARPES) signals expected in the paramagnetic (PM) Kondo phases. By analyzing the Fermi surface (FS), we observe the Lifshitz-like transition predicted previously for strong T
K at x = n

c
and we discuss the evolution of the dispersion from the dense coherent to the dilute Kondo regimes. At smaller T
K, we find that this transition marking the breakdown of coherence at x = n

c
becomes a crossover. However, we identify another transition at a smaller concentration x
⋆ where the effective mass continuously vanishes. x
⋆ separates the one-branch and the two-branches ARPES dispersions characterizing respectively dilute and dense Kondo PM regimes. The x − T
K phase diagrams are also described, suggesting that the transition at x
⋆ might be experimentally observable since magnetically ordered phases are stabilized at much lower T
K. FS reconstructions in antiferromagnetic and ferromagnetic phases are also discussed.
Probing non-Gaussianities with the high frequency tail of induced gravitational waves
Authors: Atal Vicente , Domènech Guillem 
Published: June 2021

Abstract
We investigate in detail the spectrum of gravitational waves induced by a peaked primordial curvature power spectrum generated in single-field inflationary models. We argue that the f
NL parameter can be inferred by measuring the high frequency spectral tilt of the induced gravitational waves. We also show that the intrinsically non-Gaussian impact of f
NL in ΩGW is to broaden its peak, although at a negligible level in order not to overproduce primordial black holes. We discuss possible degeneracies in the high frequency spectral tilt between f
NL and a general equation of state of the universe w. Finally, we discuss the constraints on the amplitude, peak and slope (or equivalently, f
NL) of the primordial power spectrum by combining current and future gravitational wave experiments with limits on μ distortions from the cosmic microwave background.
Possible hints of sterile neutrinos in recent measurements of the Hubble parameter
Authors: Gelmini Graciela B. , Kusenko Alexander , Takhistov Volodymyr 
Published: June 2021

Abstract
Local Universe observations find a value of the Hubble constant H
0 that is larger than the value inferred from the Cosmic Microwave Background and other early Universe measurements, assuming
known physics and the ΛCDM cosmological model. We show that additional radiation in active neutrinos produced just before Big Bang Nucleosynthesis by an unstable sterile neutrino with mass ms
= O(10) MeV can alleviate this discrepancy. The necessary masses and couplings of the sterile neutrino, assuming it mixes primarily with ντ and/or νμ neutrinos, are within reach of Super-Kamiokande as well as upcoming laboratory experiments such as NA62 and DUNE.
FIMP Dark Matter from Leptogenesis in Fast Expanding Universe
Authors: Chang Zhi-Fang , Chen Zhao-Xuan , Xu Jia-Shu , Han Zhi-Long 
Published: June 2021

Abstract
Within the framework of canonical type-I seesaw, a feebly interacting massive particle (FIMP) χ is introduced as a dark matter candidate. The leptogenesis mechanism and dark matter relic density share a common origin via decays of Majorana neutrinos N. Provided an additional species φ whose energy density red-shifts as ρφ ∝ a
-(4+n), the Hubble expansion rate is larger than the standard scenario, i.e., the Universe expands faster. The consequences of such a fast expanding Universe (FEU) on leptogenesis as well as FIMP dark matter are investigated in detail. We demonstrate a significant impact on the final baryon asymmetry and dark matter abundance due to the existence of φ for the strong washout scenario. While for the weak washout scenario, the effects of FEU are relatively small. We introduce scale factors FL
and F
χ to describe the corresponding effects of FEU. A semi-analytical approach to derive the efficiency factors η
L
and ηχ in FEU is also discussed. The viable parameter space for success thermal leptogenesis and correct FIMP DM relic density is obtained for standard cosmology and FEU. Our results show that it is possible to distinguish different cosmology scenarios for strong washout cases.
The loss surfaces of neural networks with general activation functions
Authors: Baskerville Nicholas P , Keating Jonathan P , Mezzadri Francesco , Najnudel Joseph 
Published: June 2021

Abstract
The loss surfaces of deep neural networks have been the subject of several studies, theoretical and experimental, over the last few years. One strand of work considers the complexity, in the sense of local optima, of high dimensional random functions with the aim of informing how local optimisation methods may perform in such complicated settings. Prior work of Choromanska et al (2015) established a direct link between the training loss surfaces of deep multi-layer perceptron networks and spherical multi-spin glass models under some very strong assumptions on the network and its data. In this work, we test the validity of this approach by removing the undesirable restriction to ReLU activation functions. In doing so, we chart a new path through the spin glass complexity calculations using supersymmetric methods in random matrix theory which may prove useful in other contexts. Our results shed new light on both the strengths and the weaknesses of spin glass models in this context.
Random walks on networks with preferential cumulative damage: generation of bias and aging
Authors: Eraso-Hernandez L K , Riascos A P , Michelitsch T M , Wang-Michelitsch J 
Published: June 2021

Abstract
In this paper, we explore the reduction of functionality in a complex system as a consequence of cumulative random damage and imperfect reparation, a phenomenon modeled as a dynamical process in networks. We analyze the global characteristics of the diffusive movement of random walkers on networks where the walkers hop considering the capacity of transport of each link. The links are susceptible to damage that generates bias and aging. We describe the algorithm for the generation of damage and the bias in the transport producing complex eigenvalues of the transition matrix that defines the random walker for different types of graphs, including regular, deterministic, and random networks. The evolution of the asymmetry of the transport is quantified with local information in the links and further with non-local information associated with the transport on a global scale, such as the matrix of the mean first passage times and the fractional Laplacian matrix. Our findings suggest that systems with greater complexity live longer.
Multilayer social reinforcement induces bistability on multiplex networks
Authors: Liu Longzhao , Wang Xin , Tang Shaoting , Zheng Hongwei , Zheng Zhiming 
Published: June 2021

Abstract
The social reinforcement mechanism, which characterizes the promoting effects when exposed to multiple sources in the social contagion process, is ubiquitous in information technology ecosystems and has aroused great attention in recent years. While the impacts of social reinforcement on single-layer networks are well documented, extension to multilayer networks is needed to study how reinforcement from different social circles influences the spreading dynamics. To this end, we incorporate multilayer social reinforcement into an ignorant–spreader–ignorant model on multiplex networks. Our theoretical analysis combines the pairwise method and mean-field theory and agrees well with large-scale simulations. Surprisingly, we find this complex social contagion mechanism triggers the emergence of bistability phenomena, where extinction and outbreak states coexist. In particular, the hysteresis loop of stationary prevalence occurs in this bistable region, explaining why the fight against the spread of rumors is protracted and difficult in modern society. Further, we show that the final state of bistable regions depends on the initial density of adopters, the critical value of which decreases as the contagion transmissibility or the multilayer reinforcement increases. In particular, we highlight two possible conditions for the outbreak of social contagion: to possess large contagion transmissibility, or to possess a large initial density of adopters with strong multilayer reinforcement. Our results unveil the non-negligible power of social reinforcement on multiplex networks, which sheds lights on designing efficient strategies in spreading behaviors such as marketing and promoting innovations.
Automatic clustering based approach for brain tumor extraction
Authors: Sahoo Akshya Kumar , Parida Priyadarsan 
Published: June 2021

Abstract
The brain cancer is a deadly disease affecting almost 1.7% of world’s population with top mortality rate. The basic cause of brain cancer is the abnormal growth of brain tissues in the early stage. Further, these tissues are converted into tumors. Early detection and exact location of brain tumor can assist for further therapies of brain. In this paper a computer vision-based approach is developed for exacting an exact location of the brain tumors from the MRI images. The method starts from skull stripping for removal of the outer portion of brain and segregate the white matter. Further communication with local agent (CLA) clustering technique is applied followed by morphological post processing methods for extraction of tumor regions from white matter regions of the brain. The method is tested on a publicly available MRI dataset. Quantitative and qualitative measures show that the proposed method achieves an accuracy of 99.64% as compared to others.
Volumetric Analysis of GTEM Cell for Wide Frequency Application
Authors: Pathak Hetal M , Shah Shweta N 
Published: June 2021

Abstract
In modern communication era, there are many electronic equipment all around us. The Electromagnetic Interference of other surround electronic equipment will enhance the level of noise to degrade the performance of System. In real life, this is necessary to test any equipment before it came to market. For Industrial as well as small scale for Domestic activity GTEM cell is designed for larger and smaller size of volume. Smaller volume GTEM is designed for 1-9.5 GHz while larger volume GTEM is designed for 9.5 to 18GHz frequency. As per the requirement of an EUT dimensions the cost effective and compact GTEM cell are Simulated and Analyzed.
Performance analysis of multiuser MIMO OFDM systems incorporating feedback delay and feedback error
Authors: Surya S , Kanthimathi M , Rajalakshmi B 
Published: June 2021

Abstract
In multiuser Multiple Input Multiple Output Orthogonal Frequency Division Multiplexing (MIMO-OFDM) systems the performance can be improved when full Channel State Information (CSI) is available at the transmitter. The characterization of downlink channel is estimated at the receiver and feedback to the transmitter. But the transmitter may acquire false information due to delay or errors in the feedback channel. The resulting channel capacity loss and Bit Error Rate (BER) performance are evaluated. The BER and the capacity of MIMO-OFDM systems are analyzed by varying the parameters of the system.
Simulation platform of a free-space optical network under multipath fading channel
Authors: Mallick B , Parida P , Palai G 
Published: June 2021

Abstract
This paper deals with channel modelling in free space optics (FSO) network using MATLAB 2017a. A detailed mathematical methodology to design an optical network is proposed under various small scales fading effects such as Rayleigh, and Rician fading which degrades the execution of a wireless channels. In the proposed work, the system is implemented at different sample rates, Various Doppler shifts through a flat fading channel. To modulate the data, Quadrature phase-shift keying (QPSK) modulation is used. The simulated effect of the fading channel of Rayleigh and Rician is contrasted in this paper.
Modified ML-kNN and Rank SVM for Multi-label Pattern Classification
Authors: Kassim Thanseeha , Shajee Mohan B S , Ahammed Muneer K V 
Published: June 2021

Abstract
To develop an efficient multi-label classifier is the main objective of this paper. In multi-label learning tasks such as classification, each example is associated with a set of labels, and the task is to predict the label set whose size is unknown apriory for each unseen example. In a realistic scenario each object or entity belongs to a multi-label category. Multi-Label k-Nearest Neighbor (ML-kNN), Rank-SVM (Ranking Support Vector Machine) are two popular techniques used for multi-label pattern classification. ML-kNN is a multi-label version of standard kNN and Rank SVM is a multi-label extension of standard SVM. The main aim of this work is to enhance the performance of these methods. Multi-label classifiers generally consider ranking loss, Hamming loss, one error, average precision and coverage as a performance metrics.
Hidden Markov Model energy conservation approach for continuous monitoring of vital signs in geriatric care applications
Authors: Pillai R R , Lohani R B 
Published: June 2021

Abstract
In the recent healthcare crisis engendered by the Covid19 pandemic, wireless body area networking devices have started to play a significant role in mitigating the health problems of the elderly. The energy conservation of the device during the temporary disconnection of the sensor node can play a vital role in the broader acceptance of this technology. Here, a probabilistic hidden Markov model (HMM) is used for energy conservation, a relatively less explored area of energy conservation approach within the field of wireless sensor networks. Since the vital signs of heart rate and blood pressure are highly correlated, the heart rate and blood pressure readings are taken for model development. The classification of normal and critical data is based on the probability of observation sequences in the particular model. The hidden states are estimated using the observation sequence and the HMM parameters during disconnection. Accuracy between 0.9 and 1.0 is obtained for different series. Dynamic threshold limits are included for more adaptability of the model for varying physiological conditions of the patients. The energy conservation possible using the model is discussed. This model presents a novel approach to energy conservation using HMM, which will help continuous home monitoring of vital parameters in geriatrics.
A Novel Loadless 6T-SRAM Cell with Isolated Read Port
Authors: Garg Vyom , Goel Vivek , Pandey Neeta 
Published: June 2021

Abstract
Conventional 6T SRAM cell parameters have degraded with scaling to newer technologies and reduced power supply voltages. This has led to numerous tradeoffs with respect to cell stability, performance, power, and area. In this paper, a novel Dual Port SRAM design has been introduced that aims at improving the read and write ability of the standard 6T SRAM cell. The simulations for the proposed structure have been performed on HSpice using PTM 32nm Technology node. The comparison of results with the standard cell showed an increase of 84.76% in read margins and 40.81% in the write stability. Also, the proposed design was found to be capable of writing at high frequencies as the minimum pulse width of WWL for a successful write operation was determined to be 25ps. Further, the design also improves in the areas of WTV, SVNM, WTP, SPNM
Development of Altera NIOS II Soft-core system to predict total Hemoglobin using Multivariate Analysis
Authors: Pinto C F , Parab J S , Sequeira M D , Naik G M 
Published: June 2021

Abstract
In Today’s world, Hemoglobin is measured using an invasive method. This method leads to delayed diagnosis, painful experiences for patients, and a lot of biomedical waste. To overcome these problems, an Altera NIOS II soft-core based system was built to monitor hemoglobin non-invasively. The heart of the system is NIOS II soft-core processor which was configured on the DE0 Nano FPGA board having Cyclone IV EP4CE22F17C6N. This system also has a finger probe which consists of five LED sources (670 nm, 770 nm, 810nm, 850nm and 950nm) and a photodetector (OPT101) to acquire the signal using photoplethysmography (PPG). The incoming real-time PPG signal is recorded at five different wavelengths for fifteen individual subjects. Before applying Multivariate Partial Least Square Regression (PLSR), mathematical empirical formulas was used to predict hemoglobin which gave Root Mean Square Error (RMSE) of 0.442 g/dL and the prediction accuracy of 97.05%. To further improve the system accuracy, the PLSR model was implemented on the NIOS II soft-core system. With this, the hemoglobin was predicted with an accuracy of 98.98% and a RMSE of 0.179 g/dL. The designed system was validated with Bland-Altman analysis which shows good agreement between predicted and reference hemoglobin
Miniaturised UWB MIMO antenna with improved isolation and band notch capability at 5.5 GHz
Authors: Manage Prabhakar , Naik Udaykumar , Rayar Vijay , Rudrappa Gujanatti , Kareemulla Shaik 
Published: June 2021

Abstract
A two-element planar UWB-MIMO monopole antenna is proposed utilising complimentary split ring resonator (CSRR) slot to obtain high isolation and notch at 5.5 GHz. The UWB-MIMO system comprises of two identical monopole antennas designed to achieve miniaturized size of 18 x 30 mm2. A T-shaped parasitic stub is employed to attain superior isolation among the antenna elements. CSRR slot is etched to achieve notch in WLAN range at 5.5GHz and additionally to improve impedance matching a rectangular slot was inducted on the radiators. The projected design hovers over the range 3.3GHz-14.64 GHz and attained high isolation of ≤-20 dB for 3.3 GHz-12.4 GHz and-16dB for rest of the band. The antenna system is simulated and fabricated to analyze the performance in terms of reflection coefficient and radiation pattern. The outcome testifies that the proposed design is a vastly miniaturized structure with all the capabilities of being a appropriate candidate for UWB-MIMO systems.