bluuebunny/crossref_metadata_2025_split huggingface dataset:
A superconductor/TMR composite magnetic sensor for pico-Tesla magnetic field detection
Authors: Sun Kun , Yang Lan , Li Peisen , Tao Jun , Zhang Xinmiao , Ji Minhui , Peng Junping , Pan Mengchun , Chen Dixiang , Hu Jiafei , Qiu Weicheng , Zhang Qi , Hu Yueguo 
Published: October 2022

A highly sensitive superconductor/tunnel magnetoresistance (TMR) composite magnetic sensor was designed and fabricated to satisfy the demands of detecting weak magnetic fields down to the pT range at low frequencies. First, analysis of the 1/f noise provided an optimized design scheme for the TMR unit to reduce the noise level. Then, the key structural parameters of the superconducting flux transformation amplifier (SFTA) were optimized with focus on the bonding quality between SFTA and TMR units using the finite element method to enhance the magnetic field magnification factor. An SFTA–TMR composite method with secondary alignment and multi-step bonding was proposed to fabricate the composite magnetic sensor and ensure the designed bonding gap and alignment accuracy. Experiments showed that the magnetic field sensitivity reached 5 pT/Hz0.5 (@ 13 Hz), which is beyond the highest level of superconductor/TMR composite magnetic sensors reported to date and is a further step toward the application of weak magnetic field detection.
Non-inductive plasma vertical position measurement for the 1056 s discharge on EAST
Authors: Lian H. , Liu H. Q. , Brower D. L. , Ding W. X. , Huang Y. , Wang S. X. , Li W. M. , Chu Y. Q. , Zhu R. J. , Jie Y. X. 
Published: October 2022

Vertical position stability plays a crucial role in maintaining safe and reliable plasma operation for long-pulse fusion devices. In general, the vertical position is measured by using inductive magnetic coils installed inside the vacuum vessel; however, the integration drift effects are inherent for steady-state or long-pulse plasma operation. Developing a non-magnetic approach provides a fusion reactor-relevant steady-state solution that avoids the negative impact of integration drift. In this paper, we compare the non-inductively determined vertical position achieved by line-integrated interferometer and polarimeter measurements to that employing an inductive flux loop for a 1056 s discharge recently achieved on EAST (Experimental Advanced Superconducting Tokamak). Experimental results show that the non-inductive measurement is more robust than flux loops after 300 s if the integrator is not reset to suppress integrator drift. Real-time vertical position control using the non-inductive system is proposed for the next EAST experimental campaign.
Paroemiological argumentation in Italian and French journalistic discourse
Authors: Bletsas Marina 
Published: October 2022

Abstract
Proverbs are often used in argumentation to convey an epistemic or deontic point of view. While their
argumentative potential has not failed to gain the attention of linguists, much remains to be done in terms of analyzing their
pragmatic function in single argumentative contexts and languages. With a view to this desideratum, and embracing a contrastive
perspective, I pose the question of the argumentative role of proverbs in Italian and French journalistic discourse. In a
pragma-dialectical framework, I take the rhetorical perspective to pertain to argumentation as much as the dialectical one and
show the potential of proverbs in both spheres. However, I then focus mainly the former perspective, showing how paroemiological
argumentation can help mitigate the difference of opinion especially in the case of dissent and facilitate argumentative
effectiveness thanks to protagonist-centered and antagonist-oriented strategies involving linguistic polyphony and
non-directness.
(De-)constructing New Zealand PM Jacinda Ardern’s initiative to wear the hijab after the Christchurch terrorist attack
Authors: Salahshour Neda , Serafis Dimitris 
Published: October 2022

Abstract
This paper examines the discursive construction of Prime Minister Jacinda Ardern after she wore a veil following
the unprecedented terror attack in two mosques in the city of Christchurch in 2019. The articles analyzed are collected from three
main newspapers published in New Zealand’s three main cities. Analyzed using principles and tools from Critical Discourse Studies
(CDS) and Argumentum Model of Topics (AMT) more specifically, the articles reveal key arguments from both sides i.e. in support of
and against this unparalleled initiative on behalf of a political leader in the western world. On the one hand, the majority of
the news articles under analysis portray PM’s initiative as one that attempts to mitigate tension and conflict while bringing
solidarity to a grief-stricken nation; and thus, are based on the ‘locus from ontological implications’. While the perspectives
that oppose the initiative vary from explicit racist ones that present Muslims as threat to Zealand, to those who strongly believe
such actions support the women oppression. Through a (de-)construction of the arguments opposing this move, the findings
demonstrate that the opposition towards PM’s initiative is based on two main loci namely the ‘locus from correlates’ and the
‘locus from termination and setting up’
Boundary condition analysis of first and second order topological insulators
Authors: Wu Xi , Kimura Taro 
Published: October 2022

Abstract
We analytically study boundary conditions of the Dirac fermion models on a lattice, which describe the first and second order topological insulators. We obtain the dispersion relations of the edge and hinge states by solving these boundary conditions, and clarify that the Hamiltonian symmetry may provide a constraint on the boundary condition. We also demonstrate the edge-hinge analog of the bulk-edge correspondence, in which the nontrivial topology of the gapped edge state ensures gaplessness of the hinge state.
A novel denoising method for low SNR NMR logging echo signal based on deep learning
Authors: Liu Yao , Cai Jun , Jiang Zhimin , Zhang Pu , Cheng Jingjing 
Published: October 2022

Abstract
The T
2 spectrum obtained by inversion of the nuclear magnetic resonance logging echo signal can provide various petrophysical parameters to help technicians effectively identify the type of fluid. However, raw logging data with a low signal-to-noise ratio can cause inversion results to deviate from the truth. Therefore, a deep learning denoising method is proposed to eliminate the limitations of traditional mathematical transform methods. A one-dimensional deep convolutional generative adversarial networks model is designed to fit the noise distribution of actual logging data, then generate simulation data. A multi-scale echo denoising network (MsEDNet) is designed to adaptively learn the multi-exponential decay characteristics of the signal and the optimal transform space. The denoising dataset consists of simulation data and logging data, which is applied to train MsEDNet and improve the generalization performance. With effectiveness analysis and various denoising experiments, it is validated that the proposed method has excellent denoising performance on simulation data, logging data, and water tank data.
Progress on physics understanding of improved confinement with fishbone instability at low q
95 < 3.5 operation regime in EAST
Authors: Zhang B. , Gong X. , Qian J. , Zeng L. , Xu L.Q. , Duan Y.M. , Zhang J.Y. , Hu Y.C. , Jia T.Q. , Li P. , Liang R.R. , Wang Z.H. , Zhu X. , Wang S.X. , Ma Q. , Ye L. , Huang J. , Ding R. , the EAST Team  
Published: October 2022

Abstract
Improved confinement at the low q
95 < 3.5 operation regime with fishbone instability compared to sawtooth oscillation has been observed and investigated on the EAST under the dominant electron heating condition with a tungsten divertor. The formation of an internal transport barrier in the ion thermal channel strongly correlates to the excitation of the fishbone, accompanied by reduced particle outward transport in the core region identified by a central peaked density profile. Current density distribution is found to change from a monotonic shape with q
0 < 1 during sawtooth oscillation to a central flat structure, magnetic shear s ∼ 0 at ρ < 0.4, with the fishbone instability at where the higher off-axis bootstrap current fraction might play a critical role. Linear gyrokinetic simulation by NLT code was carried out to investigate the turbulent transport characteristics, which is qualitatively in good agreement with experimental measurements from CO2 laser collective scattering diagnostics. The electron-scale trapped electron mode that dominates the turbulent transport during sawtooth is found to be stabilized with the fishbone at identical heating power and plasma configurations.
Challenges and progress in the application of physiological models for clinical decision support in cardiovascular medicine
Authors: Hose D R , Lawford PV , Halliday I , Rafiroiu D , Lungu A 
Published: October 2022

Abstract
The IUPS Physiome and the European Commission’s Virtual Physiological Human (VPH), funded under the Framework 7 programme, are just two of the major initiatives that have supported the development of physiological models for clinical decision support. There is significantprogress in the formalisation of the concept of the Digital Twin for human physiology and in processes for model personalisation, verification and validation. The VPH Institute and the Avicenna Alliance continue to promote best practice in this area. One of the most important challenges is to achieve the right level of complexity in the model. The most comprehensive models seek to capture all that is known about the physiological system, including detailed anatomy, organ interactions, control functions, and physical, chemical and biological processes. These models can be of enormous value in understanding human physiology, but can also be terribly difficult to personalise to support the clinical management of an individual. There is inevitable conflict between model complexity and the pragmatic limitation of data collection in the clinical pathway. In this presentation we make the case for a 3-axis digital twin, including recognition of the individual physiological envelope, and introduce three applications in cardiovascular medicine.
Measurements of Human Exposure to EMF from 4G systems: some experimental issues in urban environments
Authors: Betta G , Capriglione D , Cerro G , Miele G , Suka D , Ruttner M 
Published: October 2022

Abstract
Assessments of human exposure to EMF in urban environments represent one of the most complex tasks because of the factors causing large temporal variations and spatial non-uniformities of the measurement results among which are increased number of RF sources, numerous reflections, and scattering objects. In this sense, human exposure to 4G systems became a real challenge due to its current wide spreading. Following the guidelines provided by the relevant technical standards in force, this paper describes the experimental results achieved by performing a long-term analysis for several days and weeks on three network operators and three frequency bands adopted in Italy for 4G communications. In particular, the stability of the 4G pilot signal levels, i.e. PBCH, is analyzed. Indeed, such a level is involved in the maximum extrapolation techniques which should always warrant worst-case and time-independent estimations of the maximum E field. The effects of the averaging time on raw data is evaluated for quantifying its effect on the possibility of reducing the variability of human exposure assessment based on the use of the extrapolation techniques. Another important issue that is related to exposure safety requirements is the determination of compliance boundaries from RBS transmitting antennas (when put into service), mainly estimated by measurements and calculations (or simulations) for the areas accessible by the general public. In this regard, here are illustrated examples for measurement and simulation approaches for a roof terrace exposure conditions at two different locations in Austria.
Expected benefits and foreseen steps in creating energy communities in Romania
Authors: Darabant L 
Published: October 2022

Abstract
In 2019 the EU updated its energy policy (by adopting the Clean energy for all Europeans package) to enhance the transition from fossil fuels towards green energy - implementing the commitments of the EU’s Paris Agreement (adopted at the COP21 in December 2015) for reducing greenhouse gas emissions. The agreement on this new energy rulebook marked a significant step towards implementing the energy union strategy, published in 2015. Through this package, the EU has introduced the concept of energy communities in its legislation, notably as citizen energy communities and renewable energy communities. To incorporate the new regulations introduced by this package in the Romanian law, the Romanian government issued an Emergency Ordinance (143/December 28, 2021), that updates the Electrical energy and natural gas law (123/2012). The concept of energy communities is, from now on, part of our own legislation, and the creation of such communities in Romania can start, although there are still many questions regarding the effective steps to be taken in this process. This paper tries to emphasize the foreseen advantages of this new concept and how it could be implemented in our country.
Biological neural network model based on a non-linear stochastic system
Authors: Popovici C , Pătraşcu Cutaru A , Tuţă L , Roşu G , Fichte Lars Ole , Baltag O 
Published: October 2022

Abstract
As a contribution to recent activities in the field of modelling electro-biological phenomena, we would like to present an investigation on the electrical properties of a network of neuron and propose a simplified model for brain activity, based on a biological neural network represented by a non-linear system with stochastic components. The network’s fundamental element is represented by Izhikevich model, and including several types of responses, grouped into excitatory and inhibitory response. The network’s electrical activity is compared to a biological signal obtained from an electroencephalogram recording, and it is noted that the correlation between the biological and the simulated signal increases with the number of neurons in the network.
Automatic detection of melanoma by deep learning models-based feature extraction and fine-tuning strategy
Authors: Barburiceanu S , Terebeș R 
Published: October 2022

Abstract
Skin cancer is one of the most common and lethal cancers in the world. Even though melanoma accounts for a small fraction of all skin cancer types, it is currently the leading cause of skin cancer fatalities. In order to accurately identify the disease in the initial stages, dermoscopy was designed to help specialists and increase the detection rate. Deep learning has been found in recent research to be particularly beneficial in the detection of skin cancer and medical diagnostics. Within this context, we propose adopting two deep-learning algorithms to detect benign and melanoma skin conditions. The first option entails extracting features from CNN pre-trained networks and applying machine-learning classification to make predictions, while the second explores using a fine-tuning methodology combined with data augmentation. The goal of this work is to compare the two methodologies in terms of classification performance and time efficiency. A public database including dermoscopic images of melanoma and normal skin lesions is used for the experimental evaluation. The experimental evaluation reveals that pre-trained models offer superior performance in terms of accuracy and processing time.
Game-based virtual reality solution for post-stroke balance rehabilitation
Authors: Ciorap R , Andriţoi D , Casuţă A , Ciorap M , Munteanu D 
Published: October 2022

Abstract
In recent years, there has been a remarkable decline in stroke-related mortality. However, it remains one of the leading causes of death and the most prominent cause of lifelong disability in adults. This positive development results from increased accessibility to various stroke treatment options. In addition, the use of virtual reality in rehabilitation offers a possible alternative to traditional methods of medical rehabilitation of the upper limbs, improving muscle strength or balance. An early diagnosis of equilibrium deficits brings an incredible contribution to recovery. Analysis tests using stabilometric platforms have begun to be used more recently due to the advantages offered. This assessment method highlights and analyzes balance disorders and determines the body's center of gravity position through several sensors or arrays of sensors that transmit information to the processing software. This work aimed to develop a low-cost, stabilometric platform that could be used to build a recovery system using virtual reality-based games. The developed platform uses an Arduino UNO microcontroller that takes data from 4 force sensors. Two applications have been created. The first one was for balance maintenance and the second for execute balance exercises in the anteroposterior and mediolateral direction.
Observing the different optimizations in communication protocols for more efficient algorithms in Wireless Sensor Networks
Authors: Zanaj B , Peci A , Zanaj E 
Published: October 2022

Abstract
The different optimization performed for data exchange between the nodes of a wireless sensor network is necessary to reduce as much as possible the energy consumption. The battery constrain is the main challenge in this kind of network implementation. The protocol used for data communication from the source the sensing node toward the sink needs to bring an improvement. It will allow a longer lifetime duration for the network by keeping the nodes alive for a longer time. A longer the lifetime of the network allows its usability in different environment where the monitoring of different conditions maybe a necessity. But lately the Wireless Sensor Networks are used as well for tracking purposes like finding the nurses and doctors in a hospital centre. The data exchange and choices of the next sensor node to pass the data in the new algorithms apply the social behaviour of the birds, bees, ants in their search for food where those are in bunches or colonies. Also, within Wireless Sensor Networks application the nodes communicate by mimicking their social behaviour within the algorithm used for the data exchange, with the only purpose that data transmission and communication with the other nodes might not drain the battery.
Evaluation of a panoramic dental radiography properties by using Canny method
Authors: Stăncioi C M , Munteanu M , Abrudean M , Mureşan V , Bunta O 
Published: October 2022

Abstract
The main goal of this paper is to analyse the panoramic dental radiography by applying the Canny technique which is customized for this type of images and to obtain an image much more clear to interpret after processing it. From the resulted image then can be extracted all the necessary information for giving a diagnostic. The method can be extended and an application can be designed in such a way that a dental specialist can use it to better examine the characteristics of a patient's intraoral configuration. The simulations on different images hard to read by the human eye were done using the Matlab work environment. Image-processing techniques represent a very important part in this process and the best method which was successful will be detailed in this paper. Some image properties can be identified automatically even before the original image has been processed, but after the processing step, all the information and also the hidden details can be observed by a specialist. As a conclusion, each step performed and described in this article will aid in the analysis of panoramic dental radiography characteristics.
The role of sodium-glucose co-transporter-2 inhibitors in frail older adults with or without type 2 diabetes mellitus
Authors: Evans Marc , Morgan Angharad R , Davies Sarah , Beba Hannah , Strain William David 
Published: October 2022

Abstract
Sodium-glucose co-transporter-2 (SGLT2) inhibitors offer significant outcome benefits beyond glucose lowering, including reduced risk of cardiovascular death, all-cause mortality, major adverse cardiovascular events, hospitalisations for heart failure and progression of renal disease. Considering these therapeutic effects, minimal incremental risk for hypoglycaemia and simplicity of administration, this drug class appears to be an attractive therapeutic option for older adults, and post hoc analysis of trial data provides support for the use of SGLT2 inhibitors in this population. Nevertheless, despite favourable clinical trial data, there has been some hesitance in clinical practice prescribing these drugs to older frail adults due to the limited therapeutic experience in this population and insufficient long-term safety data. In this review article, we evaluate the risk–benefit profile for the use of SGLT2 inhibitors in this population and suggest that rather than being a treatment to avoid, SGLT2 inhibitors should be considered a valid therapeutic option for older frail adults with or without diabetes.
Peer-supported exercise intervention for persons with mild cognitive impairment: a waitlist randomised controlled trial (the BRAin Vitality Enhancement trial)
Authors: Li Polly W C , Yu Doris S F , Siu Parco M , Wong Schwinger C K , Chan Bernice S 
Published: October 2022

Abstract

Background
motivating older people with cognitive impairment to remain physically active is challenging.

Objective
this study aimed to examine the effects of a peer-supported exercise intervention on the cognitive function and health-related quality of life (HRQoL) of persons with mild cognitive impairment (MCI).

Design
a two-arm randomised controlled trial.

Setting and participants
community-dwelling persons with MCI were recruited from community centres for older adults in Hong Kong.

Methods
participants randomised to the intervention group received an 8-week group-based peer-supported multicomponent exercise intervention, while the waitlist control group received usual care. A battery of neuropsychological tests and the Short Form-36 were administered at baseline, immediately post-intervention and 3 months post-intervention.

Results
two hundred and twenty-nine participants were randomised to the intervention (n = 116) or control (n = 113) group. Compared with the control group, participants in the intervention group showed significantly greater improvements in processing speed and attention measured by the Colour Trails Test 1 (β = 7.213, 95% confidence interval [CI] = 2.870–11.557, P = 0.001) and working memory measured by the Digit Span Backward Test (β = 0.540, 95% CI = 0.199–0.881, P = 0.002) immediately post-intervention. The effects were sustained at 3 months post-intervention. Similarly, significantly greater improvements in sequencing and mental flexibility measured by the Colour Trails Test 2 were observed in the intervention group 3 months post-intervention (β = 6.979, 95% CI = 3.375–10.584, P &lt; 0.001). Changes in global cognition, short-term memory and HRQoL were not significant.

Conclusion
the peer-supported exercise intervention was effective at sustaining improvements in executive function, attention and working memory in persons with MCI.