bluuebunny/crossref_metadata_2025_split huggingface dataset:
Near ambient pressure photoelectron spectro-microscopy: from gas–solid interface to operando devices
Authors: Amati Matteo , Gregoratti Luca , Zeller Patrick , Greiner Mark , Scardamaglia Mattia , Junker Benjamin , Ruß Tamara , Weimar Udo , Barsan Nicolae , Favaro Marco , Alharbi Abdulaziz , Jensen Ingvild J T , Ali Ayaz , Belle Branson D 
Published: February 2021

Abstract
Near ambient pressure scanning photoelectron microscopy adds to the widely used photoemission spectroscopy and its chemically selective capability two key features: (1) the possibility to chemically analyse samples in a more realistic gas pressure condition and (2) the capability to investigate a system at the relevant spatial scale. To achieve these goals the approach developed at the ESCA Microscopy beamline at the Elettra Synchrotron facility combines the submicron lateral resolution of a Scanning Photoelectron Microscope with a custom designed Near Ambient Pressure Cell where a gas pressure up to 0.1 mbar can be achieved. In this manuscript a review of experiments performed with this unique setup will be presented to illustrate its potentiality in both fundamental and applicative research such as the oxidation reactivity and gas sensitivity of metal oxides and semiconductors. In particular, the capability to perform operando experiments with this setup opens the possibility to study operating devices and to properly address the real nature of the studied systems, because if microscopy and spectroscopy are simultaneously combined in a single technique it can yield to more conclusive results.
Measurement outcomes that do not occur and their role in entanglement transformations
Authors: Hebenstreit Martin , Englbrecht Matthias , Spee Cornelia , de Vicente Julio I. , Kraus Barbara 
Published: February 2021

Abstract
The characterization of transformations among entangled pure states via local operations assisted by classical communication (LOCC) is a crucial problem in quantum information theory for both theoretical and practical reasons. As LOCC has a highly intricate structure, sometimes the larger set of separable (SEP) maps is considered, which has a mathematically much simpler description. In the literature, mainly SEP maps consisting of invertible Kraus operators have been taken into account. In this paper we show that the consideration of those maps is not sufficient when deciding whether a state can be mapped to another via general SEP transformations. This is done by providing explicit examples of transformations among pure three- and five-qubit states, which are feasible via SEP maps containing singular Kraus operators, however, not possible via SEP maps containing solely regular Kraus operators. The key point that allows to construct the SEP maps is to introduce projective measurements that occur with probability zero on the input state. The fact that it is not sufficient to consider SEP maps composed out of regular Kraus operators even in the case of pure state transformations, also affects the results on LOCC transformations among pure states. However, we show that non-invertible Kraus operators do not help in state transformations under LOCC with finitely many rounds of classical communication, i.e. the necessary and sufficient condition for SEP transformations with invertible Kraus operators is still a necessary condition for convertibility under finite-round LOCC. Moreover, we show that the results on transformations via SEP that are not possible with LOCC (including infinitely many rounds of classical communication) presented in Hebenstreit et al 2016 Phys. Rev. A
93, 012339 are not affected.
Gravitational energy of the spherically symmetric static and charged black holes encircled by the dark energy through approximate Lie symmetries
Authors: Liaqat Asia , Hussain Ibrar 
Published: February 2021

Abstract
We investigate the gravitational energy of the Reissner-Nordström black hole encircled by dark energy using the approach of approximate Lie symmetries of second-order. We confine our calculations to following values of the equation of state parameter ω: (i)

ω

q

=
−

1

2

(quintessence regime of dark energy), (ii) ω
Λ = −1 (the pure cosmological constant regime), (iii)

ω

c

=
−

1

3

(frustrated cosmic strings network). In order to examine the gravitational energy for the Reissner-Nordström black hole spacetime encircled by the dark energy, we construct a system of second-order perturbed geodesic equations, which is done primarily by considering the mass M and charge Q of the black hole in terms of some small perturbation parameter ϵ. It is observed that we do not obtain any non-trivial approximate symmetry generator for any value of the state parameter ω, we get only trivial second-order approximate symmetry generators. As a result of these trivial approximate symmetries we get a rescaling of the proper time s which gives the rescaling of energy in the Reissner-Nordström spacetime encircled by the dark energy. It is found that for

ω

q

=
−

1

2

and ω
Λ = −1, the rescaling factor for energy is dependent on r and for

ω

c

=
−

1

3

, the rescaling factor is independent of the radial distance r. Furthermore, we investigate that the effect of cosmological constant and quintessence dark energy decreases the energy of the underlying spacetime while the equation of state parameter

ω

c

=
−

1

3

, for which the Universe is static, increases the energy of the Reissner-Nordström black hole spacetime encircled by the dark energy.
Improvements on spatial coverage and focality of deep brain stimulation in pre-surgical epilepsy mapping
Authors: Collavini Santiago , Fernández-Corazza Mariano , Oddo Silvia , Princich Juan Pablo , Kochen Silvia , Muravchik Carlos H 
Published: February 2021

AbstractObjective.Electrical stimulation mapping (ESM) of the brain using stereo-electroencephalography (SEEG) intracranial electrodes, also known as depth-ESM (DESM), is being used as part of the pre-surgical planning for brain surgery in drug-resistant epilepsy patients. Typically, DESM consists in applying the electrical stimulation using adjacent contacts of the SEEG electrodes and in recording the EEG responses to those stimuli, giving valuable information of critical brain regions to better delimit the region to resect. However, the spatial extension or coverage of the stimulated area is not well defined even though the precise electrode locations can be determined from computed tomography images.Approach.We first conduct electrical simulations of DESM for different shapes of commercial SEEG electrodes showing the stimulation extensions for different intensities of injected current. We then evaluate the performance of DESM in terms of spatial coverage and focality on two realistic head models of real patients undergoing pre-surgical evaluation. We propose a novel strategy for DESM that consist in applying the current using contacts of different SEEG electrodes (x-DESM), increasing the versatility of DESM without implanting more electrodes. We also present a clinical case where x-DESM replicated the full semiology of an epilepsy seizure using a very low-intensity current injection, when typical adjacent DESM only reproduced partial symptoms with much larger intensities. Finally, we show one example of DESM optimal stimulation to achieve maximum intensity, maximum focality or intermediate solution at a pre-defined target, and one example of temporal interference in DESM capable of increasing focality in brain regions not immediately touching the electrode contacts.Main results.It is possible to define novel current injection patterns using contacts of different electrodes (x-DESM) that might improve coverage and/or focality, depending on the characteristics of the candidate brain. If individual simulations are not possible, we provide the estimated radius of stimulation as a function of the injected current and SEEG electrode brand as a reference for the community.Significance.Our results show that subject-specific electrical stimulations are a valuable tool to use in the pre-surgical planning to visualize the extension of the stimulated regions. The methods we present here are also applicable to pre-surgical planning of tumor resections and deep brain stimulation treatments.
The study of radiation effect on Raman Distributed optical fiber Temperature Sensor
Authors: Xiang Meiqiong , Liu Yanyang , Qing Xianguo , He Zhengxi , Zhu Jialiang , He Peng , XinLv  
Published: February 2021

Abstract
The rapid development of big data and artificial intelligence technology is inseparable from the acquisition of massive basic data, and the data is acquired by sensors. The Raman Distributed optical fiber Temperature Sensor (RDTS) is a kind of sensor with many advantages, such as: anti-electromagnetic interference, intrinsic safety, small size, water and high temperature resistance. It has been applied in many fields for fast and continuous temperaturemeasurement. However, due to the rapid attenuation of transmitted light and the temperature error in radiated environment, it has not been applied innuclear field. Therefore, in order to improve the temperature accuracy of RDTS in radiated environment and provide basic data for advanced control. This paper studies the radiation effect on RDTS. Analyzesthe radiation damage mechanism and radiation damage influencing factors of RDTS. Proposes measures to improve the anti-radiation performance and provides four useful calibration methodsfortemperature error. Among them, two calibration methods have been proved right by experiments.
Design of a novel grinding end-effector for spiral welded pipe
Authors: Ayalew Getachew Demeissie , Zheng Yu , Yang Yang 
Published: February 2021

Abstract
In the spiral welded pipe manufacturing process, grinding is one of the production processes, this process proceeds by hand grinding and fixed machine grinding. Usually, those methods have impacts larboard intensive, long production cycle and unstable product qualification rate for the final product. To prevent those factors from this paper, present a newly-designed grinding machine for a spiral welded pipe manufacturing industry, the machine has equipped with a special grinding machine with the ability to grind the spiral welded pipe the inner and outer surface simultaneously of the pipe and equipped with 6DOF grinding robot. The kinematics model of grinding robot is derived and the robot joint trajectory is calculated. The simulation result shows that the grinding mechanism can perform the job without failures under the external torque, and also trajectory graph of the robot kinematics shows there is no vibration on the robot movement to perform the job.
Case studies in modular prefabrication: comparative analysis and discoveries
Authors: Gharehbaghi Koorosh , Mulowayi Erica , Rahmani Farshid , Paterno David 
Published: February 2021

Abstract
While prefabrication is the process where parts are manufactured off-site, modular construction on other hand is the utilisation of parts along with their installation to form a complete structure, such as a building. The aim of this paper is to compare case studies in prefabrication including modular construction. Subsequently, this paper reviewed five case studies around the globe. The comparison of these case studies showed that China had the fastest construction rate by manufacturing steel modules off-site. This was presumably due to the significant use of Advanced Modular Technology (AMT). Such new technique can potentially be the next era of prefabrication construction in high-rise construction. Particularly, the corporations which are either exploring or are using modular prefabrication should utilise AMT to enhance the design technique and assembly of prefabricated units.
An estimation procedure with knot selection for multivariate regression splines
Authors: Huang Tzee-Ming 
Published: February 2021

AbstractKnot selection for regression splines is crucial to the approximation power of splines. For univariate splines, many knot selection algorithms are available. However, extending those univariate algorithms to the multivariate case can be challenging. In this work, an estimation procedure with knot selection for multivariate regression splines is proposed, where the knot selection part is adapted from an existing univariate knot selection algorithm. Simulation results are included to demonstrate the performance of the proposed method.
An LSTM model for extracting hierarchical relations between words for better topic modeling
Authors: Javeed Arshad 
Published: February 2021

Abstract
Often when dealing with text data, there exists valuable information that determines the relationship between the words encountered in the corpus. The type of relationship which is sought after is the “has-a” and “is-a” relationship, with which one can build a hierarchical representation of words. Since each language has its own set of rules and syntax, extraction of the relationships ultimately boils down to understanding the syntax of the particular language and using relevant features in the process.
The paper presents a machine-learning model for understanding the language syntax and deducing the relationships between the words encountered. To be specific, a sequence modeling approach if followed, where the model receives a sequence of words and makes use of the various properties of the words to build a hierarchical graph. The algorithm described will be independent of the language, and the model should be versatile enough to be trained for different languages. In addition, the paper also describes how this information can be used to build better topic models, given a corpus of text.
Satellite disturbance detection and rejection with control moment gyros
Authors: Lee Jung-Hyung , Lee Joon-Yong , Oh Hwa-Suk 
Published: February 2021

Abstract
Uncertain external disturbances either secular or oscillating make the satellite attitude be deviated or oscillating from the mission attitude. These disturbances should be detected in short and rejected with proper counter torques of actuators. Nonlinear second order sliding mode observer is one of the good algorithms that can be used for the detection of disturbances’ magnitude and frequencies. With a control law of the integration and dipole rejection filters based on the identified disturbance information, the actuator torques can compensate the disturbances. The spacecraft attitude is then stabilized at the mission attitude within a tolerable error. In this paper, the performances of detection and rejection algorithms are checked respectively in computer simulations. The applicability is proved on a satellite ground simulator recently developed in Korea Aerospace University. The results show that the algorithms work properly with small error, which is due to the low grade of sensors and actuators.
Hierarchical graph attention network for relation extraction
Authors: Sun Hongru , Ni Wancheng , Yang Yiping 
Published: February 2021

AbstractPrevious research on relation extraction has proved the effectiveness of using dependency trees, which build non-local connections between tokens. However, the existing dependency-based models treat the dependency trees as an inherently flat graph, which causes a loss of dependency information for representing sentences. Besides, they fail to consider the fact that the importance of tokens on the dependency tree varies with different relations to be extracted. In this paper, we propose a novel hierarchical graph attention networkHierGAT, which can generate multi-level dependency trees and extract key information from them to improve relation extraction. Specifically, it contains multiple dependency-based graph attention layers, each of which takes a different dependency tree generated by an adaptive subtree pruning strategy as input, and distinguishes the importance of different tokens in a dependency tree. Finally,HierGATintegrates the output token representations of each layer with a multi-head attention mechanism, and learns sentence representation for relation extraction through a pooling layer. The experimental results demonstrate that our method outperforms state-of-the-art baselines on the benchmark datasets.
Extracting a DME area based on graph-based image segmentation and collation of OCT retinal images*
Authors: Shirokanev Alexandr , Ilyasova Nataly , Demin Nikita , Zamyckij Evgeniy 
Published: February 2021

Abstract
This paper proposes a technique for improving the localization of areas of diabetic macular edema. This study is relevant because the incidence of serious eye diseases due to diabetic macular edema is only increasing among the world’s population. The proposed method is graph-based image segmentation. Comparison of optical coherence tomography (OCT) data and retinal images is based on the search and comparison of special points on the original analyzed image and OCT analysis based on these images. Segmentation accuracy is improved by using specially selected parameters. Of these, the optimal parameters obtained in the course of the study made it possible to achieve a segmentation error of 2%.
Discriminative locality-constrained sparse representation for robust face recognition
Authors: Huang Meng , Shao Guifang , Wang Keqi , Liu Tundong , Lu Hao 
Published: February 2021

Abstract
In this paper, a new joint sparse representation method called discriminative locality-constrained sparse representation (DLSR) is proposed for robust face recognition. DLSR incorporates locality and label information of training samples into the framework of sparse representation. Locality information can distinguish dissimilarity between samples and plays an important role in image classification. Compared with the existing methods, DLSR contains more discriminative information of samples and can obtain more discriminative recognition results. Due to the use of l2-norm regularization, DLSR can obtain a closed-form solution. This makes it computationally very efficient. Experimental results based on the benchmark face databases ORL have shown that DLSR can achieve more promising performance than some state-of-the-art methods.
Comparison of Malaria Parasite Image Segmentation Algorithm Using Thresholding and Watershed Method
Authors: Jusman Yessi , Pusparini Anindita , Nazilah Chamim Anna Nur , Kanafiah Siti Nurul Aqmariah Mohd 
Published: February 2021

Abstract
Malaria is an infectious disease caused by plasmodium that lives and breeds in the red blood cells, transmitted by the Anopheles mosquito. During this time, the paramedics to diagnose symptoms use any imagery that is done manually. In the identification analysis of the malaria parasite cell infection, there is a possibility of human error factor done by paramedics because of the number of samples analyzed. This case is because the human eye tends to be tired while working continuously, leading to misclassification and treatment that is not right. Therefore, it takes a computer-based system that facilitates image processing to paramedics or laboratory technicians to identify the parasite cells and reduce human error instances. This research conducted on identification of the thresholding and watershed of segmentation method for three types of plasmodium parasite, namely Plasmodium falciparum, Plasmodium malaria, and Plasmodium vivax. This study offered modifications thresholding and watershed algorithm. The results showed the success of the technique that can effectively segment on the three types of Plasmodium malaria, which has an accuracy rate above 90% as well as the results of the computation time between the thresholding method could segment imagery for 1-2 seconds and the watershed method intelligent segmented representation for 3-4 seconds.
Health impacts of fine particles under climate change mitigation, air quality control, and demographic change in India
Authors: Dimitrova Asya , Marois Guillaume , Kiesewetter Gregor , K C Samir , Rafaj Peter , Tonne Cathryn 
Published: February 2021

Abstract
Despite low per capita emissions, with over a billion population, India is pivotal for climate change mitigation globally, ranking as the third largest emitter of greenhouse gases. We linked a previously published multidimensional population projection with emission projections from an integrated assessment model to quantify the localised (i.e. state-level) health benefits from reduced ambient fine particulate matter in India under global climate change mitigation scenarios in line with the Paris Agreement targets and national scenarios for maximum feasible air quality control. We incorporated assumptions about future demographic, urbanisation and epidemiological trends and accounted for model feedbacks. Our results indicate that compared to a business-as-usual scenario, pursuit of aspirational climate change mitigation targets can avert up to 8.0 million premature deaths and add up to 0.7 years to life expectancy (LE) at birth due to cleaner air by 2050. Combining aggressive climate change mitigation efforts with maximum feasible air quality control can add 1.6 years to LE. Holding demographic change constant, we find that climate change mitigation and air quality control will contribute slightly more to increases in LE in urban areas than in rural areas and in states with lower socio-economic development.
Energetics of critical oscillators in active bacterial baths
Authors: Gopal Ashwin , Roldán Édgar , Ruffo Stefano 
Published: February 2021

Abstract
We investigate the nonequilibrium energetics near a critical point of a non-linear oscillator immersed in an active bacterial bath. At the critical point, we reveal a scaling exponent of the average power exerted by a constant non-conservative torque

⟨

W

̇

⟩

∼

(

D

a

/
τ

)

1
/
4

, where D
a is the effective diffusivity and τ the correlation time of the bacterial bath described by a Gaussian colored noise. Other features that we investigate are the average stationary power and the variance of the work both below and above the saddle-node bifurcation. Above the bifurcation, the average power attains an optimal, minimum value for finite τ that is below its zero-temperature limit. Furthermore, we reveal a finite-time uncertainty relation for active matter which leads to values of the Fano factor of the work that can be below 2k
B
T
eff, with T
eff the effective temperature of the oscillator in the bacterial bath. We analyze different Markovian approximations to describe the nonequilibrium stationary state of the system. Finally, we illustrate our results in the experimental context by considering the example of driven colloidal particles in periodic optical potentials within an E. Coli bacterial bath.