bluuebunny/crossref_metadata_2025_split huggingface dataset:
Widening the North/South Divide? Representations of the role of the EU during the Covid-19 crisis in Spanish
media
Authors: Filardo-Llamas Laura , Perales-García Cristina 
Published: February 2022

Abstract
In this article we study the discursive construction of the EU managerial role in the early stages of the Covid-19 pandemic in four Spanish newspapers: two
published in mainland Spain – El Mundo and El País – and two published in Catalonia – La
Vanguardia and ARA. By doing a qualitative study of newspapers, this article aims to identify which
discourse strategies are used when informing about the actions and decisions taken in European political and economic fora. The
analysis identifies the three main generic frames which are used in news pieces: morality (mostly as a call for solidarity),
economic (mostly as preventing possible harm), and conflict (focused on divide(s) within (EU)rope). The activation of these frames
in the news pieces contribute to an implicit legitimation of the existence of (EU)rope as based on two core values – solidarity
and cooperation – together with a delegitimation of the actions performed by some European institutions.
Commercialising the struggle: the organisational and ideological effects of democracy assistance on opposition activism in Zimbabwe
Authors: Mataruse Prolific S. , Matthews Sally 
Published: February 2022

ABSTRACTOne of the ways in which opposition activists in Zimbabwe receive funding is through democracy assistance. Focusing on the late 1990s to 2016, this article explores the effect the receipt of such aid had on the ways in which opposition activists organise and on their ideological orientation. The authors show that the availability of such funds contributed to the commercialisation of the struggle whereby opposition activists began to view activism as a way to earn a living. Furthermore, this funding led to a decline in trust, passion and voluntarism among opposition activists. And, finally, dependence on foreign funding resulted in ideological shifts in Zimbabwean opposition parties and organisations whereby radical, left-leaning positions were abandoned in order to secure funding. The authors suggest that local strategies for funding such struggles for democracy must be given greater consideration to promote transformational possibilities and new participatory forms of democracy.
Improved accuracy of optical distance sensor based on artificial neural network applied to real-time systems
Authors: Bui Ngoc-Thang , Nguyen Thi My Tien , Nguyen Bang Le-Huy , Vu Thi Thu Ha , Nguyen Cong Hoan , Bui Quoc Cuong , Park Sumin , Choi Jaeyeop , Truong Trong Toai 
Published: February 2022

Abstract
Optical time-of-flight sensors have potential in the revolution of distance measurement. These sensors can continuously monitor the distance and track the movement of objects. However, the existing sensing methods for such distance optical sensors mainly calculate the flight time, e.g. pulse transmission and receiving time, without considering the environmental effects. Therefore, the measurement accuracy is severely reduced. There are other technologies with higher accuracy in distance measurement. Nonetheless, they are too expensive due to the high accurate power supply. In this paper, we innovatively improve the accuracy of continuous distance measurement using the artificial neural network (ANN) technique. The proposed method can be applied for very cheap optical distance sensors with analog output in a real-time system. Moreover, the proposed method can self-calibrate and be miniaturized for cheap analog sensor applications. The prototype is built with the infrared sensor GP2Y0A02YK0F and an Arduino control board (ESP32_DevC), and the ANN is implemented using the deep learning algorithm. The test results show that the distance measurement accuracy is significantly improved and the measuring range is increased from 15 to 150 cm. In addition, we calculate mean squared error, mean absolute error, mean bias error, and R
2 for further performance evaluation. The experimental results have proven the superiority of the proposed ANN method in optical distance measurement. The proposed method can be applied to many types of sensors.
Development of an experimental apparatus for flat plate drag measurements and considerations for such measurements
Authors: van Nesselrooij M , van Campenhout O W G , van Oudheusden B W , Schrijer F F J , Veldhuis L L M 
Published: February 2022

AbstractAccurately measuring small changes in aerodynamic drag over a flat surface stands at the core of the development of technologies capable of reducing turbulent friction drag. A wind tunnel drag measurement system was developed which improves significantly on the state of the art. Experimental tests demonstrated that an uncertainty of less than 0.5% ofCDat a 95% confidence level was typically achieved, already at drag values below 1 N. This was replicated in two different wind tunnels. A match with literature on riblet performance within 1% ofCDwas obtained. A crucial aspect of the design is the implementation of a correction for the pressure forces on the streamwise-facing surfaces of the test plate assembly. The flexible architecture of the system in the present realisation makes it suitable for most wind tunnels having a test section width of 400 mm or larger, which allows for accelerated development of turbulent drag reduction concepts from moderate-size low-cost facilities towards flow conditions relevant to the intended industrial application.
Nondestructive detection and analysis based on data enhanced thermography
Authors: Li Xiaoyuan , Ying Xiaowei , Zhu Wen , Liu Wei , Hou Beiping , Zhou Le 
Published: February 2022

Abstract
Machine learning and data fusion methods have played a significant role in the nondestructive testing (NDT) of composite materials in modern industries. Among them, feature extraction thermography models such as principal component thermography have been well studied and applied due to their advantages of dimensionality reduction and discriminative representation. However, current pulse thermal imaging technology can only collect limited images since the tested materials cannot usually be overheated, which also decreases the performance of the feature extraction thermography models. In this paper, an improved denoising convolutional autoencoder with U-net architecture is proposed for data enhancement purposes. Using the developed structure, enhanced images are generated, in which the deep spatial information in the original images is maintained while measurement noises are decreased simultaneously. Using the original and enhanced images together, the NDT performance based on feature extraction thermography is further improved. Finally, the feasibility and effectiveness of the proposed methods are demonstrated by two defect detection experiments on carbon fiber reinforced polymer.
Enhanced photoresponse of PVP:GaSe nanocomposite thin film based photodetectors
Authors: Demirtaş Tugay , Odacı Cem , Aydemir Umut 
Published: February 2022

Abstract
Two-dimensional materials have become the focus of attention of researchers in recent years. The demand for two-dimensional materials is increasing day by day, especially with the inadequacy of graphene in optical applications. In this context, the optical and electrical characteristics of the PVP:GaSe thin film nanocomposites were investigated. The surface morphologies of the samples were characterized by SEM, the thin film thicknesses and refractive index parameters were measured by the Ellipsometer method, the structural characteristics were obtained by XRD, and Raman and PL spectroscopy was used to determine the optical characteristics. Critical parameters of Au/PVP:GaSe/n-Si photodetector were calculated under various illumination intensities. It is observed that photodetector with PVP:%5GaSe thin film has the best performance results. According to the experimental results, its responsivity, external quantum efficiency, and detectivity values are 0.485 A W−1, %86, and 1.14 × 107 cm Hz1/2 W−1 respectively.
Local magnetic behaviour of highly disordered undoped and Co-doped Bi2Se3 nanoplates: a muon spin relaxation study
Authors: Gupta Anu , Hillier A D , Telling M T F , Srivastava S K 
Published: February 2022

Abstract
Magnetism induced by defects in nominally non-magnetic solids has attracted intense scientific interest in recent years. The local magnetism in highly disordered undoped and Co-doped topological insulator (TI) Bi2Se3 nanoplates has been investigated by muon spin relaxation (μSR). Using μSR spectroscopy, together with other macroscopic characterizations, we find that these nanoplates are composed of a core with both static fields and dynamically fluctuating moments, and a shell with purely dynamically fluctuating moments. The fluctuations in the core die out at low temperatures, while those in the shell continue till 2 K. When Bi2Se3 is doped with Co, the static magnetic component increases, whilst keeping the dual (static-plus-dynamic) nature intact. The findings indicate that highly disordered TI’s could constitute a new class of promising magnetic materials that can be engineered by magnetic impurity doping.
An estimation of phase transition
*
Authors: Ishaq Shamsa , Leplaideur Renaud 
Published: February 2022

Abstract
In (2015 Ann. Sci. Éc. Norm. Supér.
48 739–763), Bruin and Leplaideur studied a class of potentials such that the pressure function exhibit a phase transition at a parameter β

c
> 0. This paper will prove that the transition in pressure function cannot appear within the interval

0
,
2

.
Two-species competition model with chemotaxis: well-posedness, stability and dynamics
Authors: Li Guanlin , Yao Yao 
Published: February 2022

Abstract
We study a system of PDEs modelling the population dynamics of two competitive species whose spatial movements are governed by both diffusion and mutually repulsive chemotaxis effects. We prove that solutions to this system are globally well-posed, without any smallness assumptions on the chemotactic coefficients. Moreover, in the weak competition regime, we prove that neither species can be driven to extinction as the time goes to infinity, regardless of how strong the chemotaxis coefficients are. Finally, long-time behaviours of the system are studied both analytically in the weakly nonlinear regime, and numerically in the fully nonlinear regime.
DeepUCT: Complex cascaded deep learning network for improved ultrasound tomography
Authors: Prasad S , Almekkawy M 
Published: February 2022

Abstract
Ultrasound computed tomography is an inexpensive and radiation-free medical imaging technique used to quantify the tissue acoustic properties for advanced clinical diagnosis. Image reconstruction in ultrasound tomography is often modeled as an optimization scheme solved by iterative methods like full-waveform inversion. These iterative methods are computationally expensive, while the optimization problem is ill-posed and nonlinear. To address this problem, we propose to use deep learning to overcome the computational burden and ill-posedness, and achieve near real-time image reconstruction in ultrasound tomography. We aim to directly learn the mapping from the recorded time-series sensor data to a spatial image of acoustical properties. To accomplish this, we develop a deep learning model using two cascaded convolutional neural networks with an encoder–decoder architecture. We achieve a good representation by first extracting the intermediate mapping-knowledge and later utilizing this knowledge to reconstruct the image. This approach is evaluated on synthetic phantoms where simulated ultrasound data are acquired from a ring of transducers surrounding the region of interest. The measurement data is acquired by forward modeling the wave equation using the k-wave toolbox. Our simulation results demonstrate that our proposed deep-learning method is robust to noise and significantly outperforms the state-of-the-art traditional iterative method both quantitatively and qualitatively. Furthermore, our model takes substantially less computational time than the conventional full-wave inversion method.
Pedestal analysis of MAST ELMy regimes
Authors: Smith S F , Kirk A , Chapman-Oplopoiou B , Clark J G , Ham C J , Horvath L , Maggi C F , Scannell R , Saarelma S 
Published: February 2022

Abstract
Mega Ampere Spherical Tokamak (MAST) pedestal data has been analysed, where a pedestal database of 892 shots was obtained, using the upgraded MAST Thomson scattering (TS) diagnostic. Various edge localised mode (ELM) types are discussed, where characteristics and trends of MAST pedestals are shown. The data from the upgraded TS diagnostic confirms pedestal characteristics found in earlier analysis, using previous TS systems. Using the database, calculations of the bootstrap current are obtained using the different analytical formulae (Sauter and Redl), and comparisons are performed. The upgraded MAST TS system now spans the full plasma mid-plane, such that direct comparisons between inboard and outboard pedestals can be obtained, and asymmetries in the density pedestal width were found. To increase confidence in spherical tokamak pedestal predictions, the assumptions of Europed have been validated from the MAST pedestal data, and a value for the kinetic ballooning mode constraint (

C
∼
0.145

) has been obtained. The first spherical tokamak pedestal predictions were performed in Europed and compared to experimental values. Using C = 0.145 the temperature pedestal height was predicted to within 10% of the experimental value. In addition type II ELMs on MAST are analysed, and stability analysis and parameter scans have been performed using ESSIVE. Similar magneto-hydrodynamic (MHD) stability properties are observed for type I and type II ELMs, originating from the mixed ELM regimes; it is therefore difficult to distinguish these ELMs using the ideal MHD codes.
Probing depth in diffuse reflectance spectroscopy of biotissues: a Monte Carlo study
Authors: Kurakina Daria , Perekatova Valeriya , Sergeeva Ekaterina , Kostyuk Alexey , Turchin Ilya , Kirillin Mikhail 
Published: February 2022

Abstract
Diffuse reflectance spectroscopy (DRS) is an optical imaging modality based on extraction of tissue structural and functional information from back-reflectance spectra. In this paper we analyze the spectral dependence of DRS probing depth for different source-detector separations (SDSs) in the range of 1.5–7.0 mm by means of Monte Carlo simulations. The simulated spectra are employed to analyze the effect of the selected spectral range on the accuracy of oxygen saturation (StO2) reconstruction for different parameters of skin. It is shown that the probing depth varies in the range of 1–4 mm depending on SDS and tissue parameters, and in the hemoglobin absorption band for particular medium configuration it demonstrates a 2-fold decrease as compared to the neighboring spectral ranges. Comparison of different spectral ranges for StO2 reconstruction from the measured spectra at different SDSs demonstrated that the range of 480–600 nm and the full range of 480–900 nm benefit over near infrared (NIR) range (700–900 nm) in the reconstruction accuracy. The 480–600 nm range provides the best reconstruction accuracy for low blood volume content, while the full range of 480–900 nm provides better accuracy for larger blood volume content. The comprehensive study of the spectral dependency of probing depth in DSR for SDSs in the range of 1.5–7.0 mm based on MC simulations for multi-layered skin model depending on skin layers properties and numerical aperture combined with analysis of StO2 reconstruction accuracy was conducted for the first time to our knowledge.
Dynamic brain functional network based on EEG microstate during sensory gating in schizophrenia
Authors: Chang Qi , Li Cancheng , Zhang Jicong , Wang Chuanyue 
Published: February 2022

Abstract

Objective. Cognitive impairment is one of the core symptoms of schizophrenia, with an emphasis on dysfunctional information processing. Sensory gating deficits have consistently been reported in schizophrenia, but the underlying physiological mechanism is not well-understood. We report the discovery and characterization of P50 dynamic brain connections based on microstate analysis. Approach. We identify five main microstates associated with the P50 response and the difference between the first and second click presentation (S1-S2-P50) in first-episode schizophrenia (FESZ) patients, ultra-high-risk individuals (UHR) and healthy controls (HCs). We used the signal segments composed of consecutive time points with the same microstate label to construct brain functional networks. Main results. The microstate with a prefrontal extreme location during the response to the S1 of P50 are statistically different in duration, occurrence and coverage among the FESZ, UHR and HC groups. In addition, a microstate with anterior–posterior orientation was found to be associated with S1-S2-P50 and its coverage was found to differ among the FESZ, UHR and HC groups. Source location of microstates showed that activated brain regions were mainly concentrated in the right temporal lobe. Furthermore, the connectivities between brain regions involved in P50 processing of HC were widely different from those of FESZ and UHR. Significance. Our results indicate that P50 suppression deficits in schizophrenia may be due to both aberrant baseline sensory perception and adaptation to repeated stimulus. Our findings provide new insight into the mechanisms of P50 suppression in the early stage of schizophrenia.
Adaptive polymer fiber neural device for drug delivery and enlarged illumination angle for neuromodulation
Authors: Sui Kunyang , Meneghetti Marcello , Kaur Jaspreet , Sørensen R J F , Berg Rune W , Markos Christos 
Published: February 2022

Abstract

Objective. Optical fiber devices constitute significant tools for the modulation and interrogation of neuronal circuitry in the mid and deep brain regions. The illuminated brain area during neuromodulation has a direct impact on the spatio-temporal properties of the brain activity and depends solely on the material and geometrical characteristics of the optical fibers. In the present work, we developed two different flexible polymer optical fibers (POFs) with integrated microfluidic channels (MFCs) and an ultra-high numerical aperture (UHNA) for enlarging the illumination angle to achieve efficient neuromodulation. Approach. Three distinct thermoplastic polymers: polysulfone, polycarbonate, and fluorinated ethylene propylene were used to fabricate two step-index UHNA POF neural devices using a scalable thermal drawing process. The POFs were characterized in terms of their illumination map as well as their fluid delivery capability in phantom and adult rat brain slices. Main results. A 100-fold reduced bending stiffness of the proposed fiber devices compared to their commercially available counterparts has been found. The integrated MFCs can controllably deliver dye (trypan blue) on-demand over a wide range of injection rates spanning from 10 nl min−1 to 1000 nl min−1. Compared with commercial silica fibers, the proposed UHNA POFs exhibited an increased illumination area by 17% and 21% under 470 and 650 nm wavelength, respectively. In addition, a fluorescent light recording experiment has been conducted to demonstrate the ability of our UHNA POFs to be used as optical waveguides in fiber photometry. Significance. Our results overcome the current technological limitations of fiber implants that have limited illumination area and we suggest that soft neural fiber devices can be developed using different custom designs for illumination, collection, and photometry applications. We anticipate our work to pave the way towards the development of next-generation functional optical fibers for neuroscience.
Algorithm and hardware considerations for real-time neural signal on-implant processing
Authors: Zhang Zheng , Savolainen Oscar W , Constandinou Timothy G 
Published: February 2022

Abstract

Objective. Various on-workstation neural-spike-based brain machine interface (BMI) systems have reached the point of in-human trials, but on-node and on-implant BMI systems are still under exploration. Such systems are constrained by the area and battery. Researchers should consider the algorithm complexity, available resources, power budgets, CMOS technologies, and the choice of platforms when designing BMI systems. However, the effect of these factors is currently still unclear. Approaches. Here we have proposed a novel real-time 128 channel spike detection algorithm and optimised it on microcontroller (MCU) and field programmable gate array (FPGA) platforms towards consuming minimal power and memory/resources. It is presented as a use case to explore the different considerations in system design. Main results. The proposed spike detection algorithm achieved over 97% sensitivity and a smaller than 3% false detection rate. The MCU implementation occupies less than 3 KB RAM and consumes 31.5 µW ch−1. The FPGA platform only occupies 299 logic cells and 3 KB RAM for 128 channels and consumes 0.04 µW ch−1. Significance. On the spike detection algorithm front, we have eliminated the processing bottleneck by reducing the dynamic power consumption to lower than the hardware static power, without sacrificing detection performance. More importantly, we have explored the considerations in algorithm and hardware design with respect to scalability, portability, and costs. These findings can facilitate and guide the future development of real-time on-implant neural signal processing platforms.
Low-cost portable system for measuring thermal conductivity of building
Authors: Palo-Tejada E , Puma A , Campos-Falcon V , Guzman A , Perez R , Tunti J 
Published: February 2022

Abstract
The developed system allows to measure the thermal conductivity of solid materials used as thermal insulators in building bioclimatic houses on high Andean zones. A unidirectional heat flow model through a sample of dimensions 4.0 cm x 4.2 cm x 1.35 cm has been considered. K-type thermocouples were used to measure the temperature’s gradient. The obtained values were: 0.97 Wm−1°C−1 for glass, 0.38 Wm−1°C−1 in the ignimbrite, 0.58 Wm−1°C−1 for the roof brick and 0.34 Wm−1°C−1 in the adobe with Stipa ichu. These materials have been evaluated considering their abundance and use in house building on the Arequipa department high zones.
Energy and economic evaluation of a middle-sized CSP parabolic field in an agro-industrial company
Authors: Torres Vidaurre A V , Saettone E 
Published: February 2022

Abstract
The energy assessment carried out in a middle-sized CSP parabolic field of 120 m2 is presented; it provides pre-heating water at 70°C to the boilers of the lemon essential oil extraction process in an agro-industrial company located in Piura, at the border of Sechura desert in Peru. The parabolic cylindrical solar concentrators are made with glass reflectors, an automatic solar tracking system, and collector tubes through which water flows. It was measured that each collector converts solar energy and transfer it as a thermal energy to the water with an average efficiency of 18.1%. Considering this result, theoretically the whole solar field could provide 550.37 GJ/year for water preheating, which is equivalent to saving 28151.8 liters of LPG, and 46.87 tons of CO2 released to the environment. However, after a year of operation, the solar field provided only 99.59 GJ for water preheating, saving 4 705.26 liters of LPG, equivalent to stop emitting 7.69 tons of CO2 to the environment. An overall thermal energy efficiency of the CSP solar field in 18.1% was estimated. According to the financial assessment with the actual annual data, the period of recovery of the investment is estimated to be 4.4 years, 3.6 more years than theoretical projection.