bluuebunny/crossref_metadata_2025_split huggingface dataset:
Chiral anomaly induced magnetoconductances in an irradiated type-I Weyl semimetal
Authors: Sen Rounak , Kar Satyaki 
Published: September 2022

Abstract
Magneto conductivities in Weyl semimetals (WSMs) in presence of small fields are studied using quasi-classical Boltzmann transport equations. Following such formalism here we consider irradiation via circularly polarized light on a two-node time reversal breaking WSM already under a dc/static electric field and study the magneto-transport properties due to the presence of chiral anomaly. Chiral anomaly affects both longitudinal magnetoconductivity as well as planar Hall conductivity. As our field set-up causes continuous time variation in the relative orientation between the fields, one naturally expects interesting magneto-transport behavior for different field strengths and tilting. The type-I tilting that we study here displays both positive and negative magnetoconductances depending on the field strengths and time. Furthermore, we find that a direct temporal tuning of the irradiated field strengths can lead to fluctuating magneto-transport behavior which can be easily improvised and checked in the laboratories.
Adaptive single-mode variational mode decomposition and its applications in wheelset bearing fault diagnosis
Authors: Li Cuixing , Liu Yongqiang , Liao Yingying , Liu Wenpeng 
Published: September 2022

Abstract
In recent years, many studies on variational mode decomposition (VMD) have mainly focused on choosing the number of modes and balancing parameter, while less research focuses on the internal properties of VMD. This paper proposes an adaptive single-mode VMD (ASMVMD) method based on the convergence characteristics of VMD and the adaptivity of particle swarm optimization (PSO). Firstly, we study the convergence characteristics of single-mode VMD and find that the U-shaped convergence region related to fault impact is very wide in the whole frequency domain. Secondly, based on the characteristics of the U-shaped convergence region, a new population position initialization strategy is proposed. Finally, the improved PSO is used to optimize the initial center frequency and balancing parameter of single-mode VMD. The effectiveness of the proposed method is verified by analyzing the simulated signal and wheelset bearing fault signals. Compared with the fast kurtogram and Autogram, it is shown that ASMVMD has a stronger capability of fault feature extraction.
Towards label-efficient automatic diagnosis and analysis: a comprehensive survey of advanced deep learning-based weakly-supervised, semi-supervised and self-supervised techniques in histopathological image analysis
Authors: Qu Linhao , Liu Siyu , Liu Xiaoyu , Wang Manning , Song Zhijian 
Published: September 2022

Abstract
Histopathological images contain abundant phenotypic information and pathological patterns, which are the gold standards for disease diagnosis and essential for the prediction of patient prognosis and treatment outcome. In recent years, computer-automated analysis techniques for histopathological images have been urgently required in clinical practice, and deep learning methods represented by convolutional neural networks have gradually become the mainstream in the field of digital pathology. However, obtaining large numbers of fine-grained annotated data in this field is a very expensive and difficult task, which hinders the further development of traditional supervised algorithms based on large numbers of annotated data. More recent studies have started to liberate from the traditional supervised paradigm, and the most representative ones are the studies on weakly supervised learning paradigm based on weak annotation, semi-supervised learning paradigm based on limited annotation, and self-supervised learning paradigm based on pathological image representation learning. These new methods have led a new wave of automatic pathological image diagnosis and analysis targeted at annotation efficiency. With a survey of over 130 papers, we present a comprehensive and systematic review of the latest studies on weakly supervised learning, semi-supervised learning, and self-supervised learning in the field of computational pathology from both technical and methodological perspectives. Finally, we present the key challenges and future trends for these techniques.
Current best estimates of beam quality correction factors for reference dosimetry of clinical proton beams
Authors: Palmans Hugo , Lourenço Ana , Medin Joakim , Vatnitsky Stanislav , Andreo Pedro 
Published: September 2022

Abstract

Objective. To review the currently available data on beam quality correction factors,

k

Q

,

for ionization chambers in clinical proton beams and derive their current best estimates for the updated recommendations of the IAEA TRS-398 Code of Practice. Approach. The reviewed data come from 20 publications from which

k

Q

values can be derived either directly from calorimeter measurements, indirectly from comparison with other chambers or from Monte Carlo calculated overall chamber factors,

f

Q

.

For cylindrical ionization chambers, a distinction is made between data obtained in the centre of a spread-out Bragg peak and those obtained in the plateau region of single-energy fields. For the latter, the effect of depth dose gradients has to be considered. To this end an empirical model for previously published displacement correction factors for single-layer scanned beams was established, while for unmodulated scattered beams experimental data were used. From all the data, chamber factors,

f

Q

,

and chamber perturbation correction factors,

p

Q

,

were then derived and analysed. Main results. The analysis showed that except for the beam quality dependence of the water-to-air mass stopping power ratio and, for cylindrical ionization chambers in unmodulated beams, of the displacement correction factor, there is no remaining beam quality dependence of the chamber perturbation correction factors

p

Q

.

Based on this approach, average values of the beam quality independent part of the perturbation factors were derived to calculate

k

Q

values consistent with the data in the literature. Significance. The resulting data from this analysis are current best estimates of

k

Q

values for modulated scattered beams and single-layer scanned beams used in proton therapy. Based on this, a single set of harmonized values is derived to be recommended in the update of IAEA TRS-398.
Small animal photon counting cone-beam CT on a preclinical radiation research platform to improve radiation dose calculation accuracy
Authors: Hu Xiaoyu , Zhong Yuncheng , Lai Youfang , Shen Chenyang , Yang Kai , Jia Xun 
Published: September 2022

Abstract

Objective. Cone beam CT (CBCT) in preclinical small animal irradiation platforms provides essential information for image guidance and radiation dose calculation for experiment planning. This project developed a photon-counting detector (PCD)-based multi(3)-energy (ME-)CBCT on a small animal irradiator to improve the accuracy of material differentiation and hence dose calculation, and compared to conventional flat panel detector (FPD)-based CBCT. Approach. We constructed a mechanical structure to mount a PCD to an existing preclinical irradiator platform and built a data acquisition pipeline to acquire x-ray projection data with a 100 kVp x-ray beam using three different energy thresholds in a single gantry rotation. We implemented an energy threshold optimization scheme to determine optimal thresholds to balance signal-to-noise ratios (SNRs) among energy channels. Pixel-based detector response calibration was performed to remove ring artifacts in reconstructed CBCT images. Feldkamp–Davis–Kress method was employed to reconstruct CBCT images and a total-variance regularization-based optimization model was used to decompose CBCT images into bone and water material images. We compared dose calculation results using PCD-based ME-CBCT with that of FPD-based CBCT. Main results. The optimal nominal energy thresholds were determined as 26, 56, and 90 keV, under which SNRs in a selected region-of-interest in the water region were 6.11, 5.91 and 5.93 in the three energy channels, respectively. Compared with dose calculation results using FPD-based CBCT, using PCD-based ME-CBCT reduced the mean relative error from 49.5% to 16.4% in bone regions and from 7.5% to 6.9% in soft tissue regions. Significance. PCD-based ME-CBCT is beneficial in improving radiation dose calculation accuracy in experiment planning of preclinical small animal irradiation researches.
Kinetic investigation of the planar multipole resonance probe under arbitrary pressure
Authors: Wang Chunjie , Friedrichs Michael , Oberrath Jens , Brinkmann Ralf Peter 
Published: September 2022

Abstract
A new plasma diagnostic tool called planar multipole resonance probe (pMRP) has been proposed in the past decade. It has a minimally invasive structure and allows simultaneous measurement of electron density, temperature, and collision frequency. Previous work has investigated the behavior of the pRMP by the Drude model, which misses kinetic effects, and the collisionless kinetic model, which misses collisional damping. To further study the pMRP at arbitrary pressure, a collisional kinetic model is proposed in this paper. The electron dynamics is described by the kinetic equation, which considers the electron-neutral elastic collision. Under the electrostatic approximation, the kinetic equation is coupled to the Poisson equation. The real part of the general complex admittance is calculated to describe the spectral response of the probe–plasma system. The calculated spectra of the idealized pMRP demonstrate that this collisional kinetic model can capture both collisionless kinetic damping and collisional damping. This model overcomes the limitations of the Drude model and the collisionless kinetic model and allows discussion of the validity of simpler models.
Maximum DC operating current degradation and magnetization loss of no-insulation (RE)Ba2Cu3O
x
coil under AC axial background magnetic fields
Authors: Xue Wenbo , Fu Yutong , Lu Zhen , Yang Qingqing , Li Ke , Zhao Yue , Wang Yawei 
Published: September 2022

Abstract
No-insulation (NI) high-temperature superconductor (HTS) coils show a great advantage on enhanced thermal stability during quenches. It is inevitably exposed to ripple AC magnetic fields in some applications, such as synchronous machines, tokamak magnets and maglev trains. The AC applied fields can induce an eddy current in NI coils due to the absence of turn-to-turn insulation. This eddy current may cause considerable maximum DC operating current degradation and additional magnetization loss in NI coils, which are still unclear. In this paper we study this issue using both experiments and simulations. An experimental platform is built to measure the maximum operating current of HTS coils exposed to AC axial applied fields, and the results show that the axial AC applied fields can lead to a significant maximum operating current degradation (22.9% in this study) on the NI HTS coil due to the eddy current induced even though the field is parallel to tape’s ab-plane and has a very low amplitude and frequency (26.88 mT/50 Hz). Meanwhile, this low applied field has little effect on the critical current of insulated HTS coils. A numerical model is applied to elucidate the underlying physical mechanism of this phenomenon, and the magnetization loss induced by an additional transport current is analyzed using this model. The influence of graded turn-to-turn resistivity technique is also investigated, and the results show that this technique can effectively prevent the maximum operating current degradation and reduce the magnetization loss of NI HTS coils exposed to AC axial applied fields.
CRPropa 3.2 — an advanced framework for high-energy particle propagation in extragalactic and galactic spaces
Authors: Alves Batista Rafael , Becker Tjus Julia , Dörner Julien , Dundovic Andrej , Eichmann Björn , Frie Antonius , Heiter Christopher , Hoerbe Mario R. , Kampert Karl-Heinz , Merten Lukas , Müller Gero , Reichherzer Patrick , Saveliev Andrey , Schlegel Leander , Sigl Günter , van Vliet Arjen , Winchen Tobias 
Published: September 2022

Abstract
The landscape of high- and ultra-high-energy astrophysics has changed in the last decade, largely due to the inflow of data collected by large-scale cosmic-ray, gamma-ray, and neutrino observatories. At the dawn of the multimessenger era, the interpretation of these observations within a consistent framework is important to elucidate the open questions in this field. CRPropa 3.2 is a Monte Carlo code for simulating the propagation of high-energy particles in the Universe.
This version represents a major leap forward, significantly expanding the simulation framework and opening up the possibility for many more astrophysical applications. This includes, among others: efficient simulation of high-energy particles in diffusion-dominated domains, self-consistent and fast modelling of electromagnetic cascades with an extended set of channels for photon production, and studies of cosmic-ray diffusion tensors based on updated coherent and turbulent magnetic-field models. Furthermore, several technical updates and improvements are introduced with the new version, such as: enhanced interpolation, targeted emission of sources, and a new propagation algorithm (Boris push). The detailed description of all novel features is accompanied by a discussion and a selected number of example applications.
DC cable cross-section selection for PV plants
Authors: Akšamović A , Odžak S , Tihak A , Grebović S , Konjicija S 
Published: September 2022

Abstract
This paper analyzes the problem of DC cable selection in photovoltaic (PV) plants. PV plants can have tens of kilometres of one-way cables that are important parts of the system. The currents flowing through these cables can reach values of several hundred amps. Losses incurred on DC cables are up to 1%, which can be significant when measuring power loss during the operating period. Reduction of these losses can be achieved by increasing the cross-section of the cable. The paper describes the requirements set by the standards for selecting cable cross-sections. An analytical criterion function that connects electricity losses and cable crosssection were deduced. This function depends on several parameters such as electricity price, cable price, the average number of sunny hours per year, average amount of electricity through cable, interest rate, loan repayment period, and plant operation period. Several cases with the analysis of the obtained results are presented.
Comparative analysis of energy indicators based on engineering model-oriented design of traction motors
Authors: Koeva D Y , Stoyanov G S , Ratchev S R , Slavov D S 
Published: September 2022

Abstract
Paper deals with a comparative analysis of energy and mass-size indicators of virtual prototypes of two traction electric motors, with a view to their application to electric transportation vehicles. For this purpose, specialized software is used, allowing electromagnetic, structural and thermal optimization according to certain criteria. In conclusion, the results of the comparative analysis are summarized.
Investigation of the influence of climatic conditions on the accuracy of acousto-optic trace route localization methods for all-dielectric optic cables
Authors: Gureev V O , Dashkov M V , Gubareva O Y 
Published: September 2022

Abstract
In the conditions of long-term operation of cable communication lines, the problem of timely maintenance of cable communication lines becomes relevant. Maintenance at minimum cost and maximum efficiency requires precise cable tracing methods. The paper considers the results of evaluating the effectiveness of acousto-optical methods for searching for the route of laying an all-dielectric optical cable laid in a package of microtubes underground. Amplitude and phase algorithms for localizing the route of laying an all-dielectric cable are considered. The results of measurements of the parameters of a distributed acoustic sensor on a test site in various climatic conditions are investigated.
Generations of human-computer interactions: evolution, tendencies and perspectives
Authors: Hristov H , Stavrev S 
Published: September 2022

Abstract
In this paper, we present the usability evolution of human-computer interactions. In addition, we group the various user interfaces of human-computer interaction into two generations with three classes each. The most user interfaces for human-computer interaction are assigned into a class depending on objective criteria scores, such as technical literacy level, level of natural interactions, user learning curve and UI’s ability to adapt. In addition, current tendencies for HCI are presented and future perspectives are discussed. Finally, we summarize the achieved results and draw conclusions.
Stress testing of Docker containers running on a Windows operating system
Authors: Sergeev A , Rezedinova E , Khakhina A 
Published: September 2022

Abstract
At the moment, Docker technology is becoming more prevalent in the Windows environment. The pertinent topic in this regard is how Docker containers running on the Windows operating system would behave in the event of a resource deficit. The article discusses circumstances in which there is insufficient processor or RAM to service all running containers. It is proposed to employ stress and volume testing to investigate the stability and reliability of Docker containers. The purpose of stress testing is to determine how the system behaves when the load on the application is greatly increased in comparison to what was initially expected. By delivering enormous amounts of data for processing, volume testing is accomplished. To assess container performance during stress testing, a Prometheus-based technology stack is used. Docker containers running in a Windows system have been shown to operate predictably under extreme load conditions. As the processor load increases, the performance of the containerized program drops proportionately to the decrease in processor time allocated. When there is insufficient RAM to run all containers, Docker uses virtual memory to dynamically distribute memory amongst containers. If a container's execution is halted due to a lack of available RAM on the system, the container's execution is terminated. Other containers continue to function normally.
Blockchain and IoT integration for smart transportation
Authors: Valchanov H , Aleksieva V 
Published: September 2022

Abstract
The safe transport of special and dangerous cargos is essential for the ecological environment and human health. Modern solutions are based on monitoring of the parameters of their transport with sensors in real time, which allows rapid response to unexpected events. Despite the information available from the sensors, the process of proving an insurance event and paying compensation is the same as for other insurances. This paper proposes a blockchain and IoT based model that chronologically records the data from the sensors located at the vehicle with goods, and the smart contract which sends timely signals to stakeholders (including the insurer) when the parameters of the sensors exceed the set thresholds. An experimental implementation on HyperLedger Fabric is presented, which proves the applicability of the proposed model.
Privacy preserving knowledge graph for healthcare applications
Authors: Sharma N , Bhatt R 
Published: September 2022

AbstractKnowledge graphs in healthcare applications help all the stakeholders in the healthcare domain. The doctors can consult across various hospitals for a particular scenario or can query the knowledge graph for the history of the patients. Similarly, the patients can query the knowledge graph through well-defined interface or a Chabot system for location of the nearest doctor with a high rating. The physicians can query the knowledge graph for a generic drug family or detecting salt of a particular drug. The paper proposes architecture for knowledge graph in healthcare domain. Further, privacy preserving for a medical domain is an essential requirement. The paper proposes privacy preserving schemes for knowledge graph for healthcare applications.
A method for drone positioning for water areas caption based on find lake in images
Authors: Boychev I , Spasova G 
Published: September 2022

Abstract
This article presents a method for automatically positioning an unmanned aerial vehicle in 3D space. The aim is to capture lake-type water sources, using maximum coverage of the water source in the images taken by the aircraft camera. The method is based on recognizing a water object in a series of images and finding one in which the water source occupies the maximum area. For the implementation of the method the software environment MATLAB is used.
An approach of energy self-sufficiency at sports facilities
Authors: Karapidakis E , Apostolakis S , Vidakis N 
Published: September 2022

Abstract
Sports facilities are special cases of large-scale building complexes that demand large amounts of energy and power. This is due to the specific requirements of the thermal energy and the different kind of several activities that need considerable high load demands in relatively short time. Energy self-sufficiency of a building complex is defined as the ability to fulfil its own energy needs. This paper evaluates the energy consumption of the Olympic Athletic Center of Athens and proposes ways to support and enhance its operation, introducing the self-sufficiency concept, where load demand will be served by energy sources from the internal grid of the sport center, targeting to the highest possible autonomous operation. To achieve the minimum imports from the utility grid, the paper proposes the operation of a CHP unit and the installation of photovoltaics (PV), with the support of battery storage system and the existing gensets of the facility.
Increasing building`s self-sufficiency rates through PV plus storage hybrids
Authors: Kisyov P 
Published: September 2022

Abstract
Decarbonizing the building stock is of utmost importance for achieving sustainability as buildings are holding an important role for the clean energy transition. In this paper, the impact on the electrical consumption and building related CO2 emissions are analysed through real measurements by taking the effect from the implementation PV plus battery energy storage hybrids within 5 residential buildings in Plovdiv area. Increased self-sufficiency rates are quantified for a period of 3 years under pure self-consumption mode, where no power sells are taking place. Indicators such as monthly and yearly self-sufficiency rates with and without storage are compared. Building`s related CO2 avoidance are also compared in two scenarios-with and without battery energy storage system.
Comparative analysis of thermal comfort in the traditional and smart buildings
Authors: Dębska L 
Published: September 2022

Abstract
All the constantly growing thermal requirements of people pose new challenges for designers in the field of modern and smart construction. The main idea of such buildings is to ensure the best possible conditions for the internal environment, especially in public facilities. In Poland, the majority of university buildings are traditional buildings that have been modernized, thus increasing the feeling of thermal comfort by people. The aim of this article is to conduct a comparative analysis of two rooms, for the smart building "Energis" and the traditional building "B" at the Kielce University of Technology. The testo 400 device was used to carry out the study, which, through parameters taken from the environment, enabled the calculation using the ISO 7730 standard, Predicted Mean Vote (PMV) and anonymous questionnaires from which an averaged Thermal Sensation Vote (TSV). The temperature of the first room was 26.7°C, and the temperature of the second was 23.6°C. The results turned out to be intriguing as the analysis showed that the students were not satisfied with the conditions in the smart building.