bluuebunny/crossref_metadata_2025_split huggingface dataset:
Lidar detection and characterization of multi-type aerosol layers in the troposphere above Sofia, Bulgaria
Authors: Deleva A , Peshev Z , Dreischuh T , Vulkova L 
Published: April 2021

Abstract
Aerosols can directly and strongly affect the atmospheric energy budget, the climatic processes, the ecological state of the environment, and the biosphere and human health. This is why the detection and identification of aerosols in terms of type and origin and their optical and microphysical characterization are of great scientific and practical importance. Lidars are a widely recognized and proven tool for detecting and studying atmospheric aerosols. In this paper, we present results of lidar detection and characterization of aerosol layers present in the troposphere over the city of Sofia. The measurements were performed at the wavelengths of 1064 nm and 532 nm by using the Nd:YAG-laser based lidar of Sofia lidar station, part of the European Aerosol Research Lidar Network (EARLINET) and the Aerosol, Clouds and Trace Gases Research Infrastructure (ACTRIS). Time-averaged vertical profiles of the aerosol backscatter coefficient and the backscatter-related Ångström exponent were retrieved and analyzed. Color-coded height-time diagrams of the vertical mass distribution in the observed layers and its temporal dynamics were also obtained. Based on information from forecast models, it is concluded that the aerosol layers registered contained marine aerosols, forest fire smoke, indirectly and directly transported dust from Sahara, as well as continental, regional and local aerosols from different sources.
Structural characterization of collagen using polarization-resolved second harmonic generation (SHG) microscopy
Authors: Mazumder N , Sindhoora K M , Kao F-J 
Published: April 2021

Abstract
Second harmonic generation (SHG) microscopy is an effective analytical tool for a detailed investigation of the microscopic structure of non-centrosymmetric molecules. We developed a four-channel photon-counting-based Stokes polarimeter integrated to the SHG microscope for spatial characterization of polarization effects in the SH signal. We implemented Stokes-vector-based polarization-resolved SHG imaging to perform quantitative polarimetry, with a view to applications in biomedicine, which can measure the full polarization state of the SH light. In this work, we describe the application of a Stokes-vector-based four-channel photon counting SHG microscope to determine the molecular interpretation of the SH light from collagen in normal, scar, and keloid tissue.
Low-level laser therapy in cases of burning mouth syndrome
Authors: Balcheva M , Balcheva G , Panov V , Madjova C 
Published: April 2021

Abstract
Burning mouth syndrome is an intraoral burning sensation which develops in the absence of mucosal changes. It is a chronic condition and, in most of the cases, it is idiopathic – no cause or mechanism can be identified and no effective treatment can be prescribed. A variety of therapeutic approaches have been applied – cognitive-behavioral therapy, different drugs and supplements, acupuncture, lasers – none of them has achieved a definitive solution of the problem. This leads to anxiety, altered pain perception, and, therefore, reduced quality of life of the affected patients. The aim of this study is to present low-level laser therapy as a pain control option in patients with burning mouth syndrome. We reveal the potential of a diode laser to reduce the unpleasant burning sensation. We also apply laser therapy on patients with primary burning mouth syndrome. The affected sites on the oral mucosa in the selected cases are various – tongue, lower lip, upper lip, palate, cheeks. They are irradiated 10 times (two or three times a week) by an infrared laser (λ = 904 nm) and a red laser (λ = 658 nm). The probe is kept in contact with the tissue and the mucosal surface is scanned during the irradiation. The burning intensity is evaluated through a visual analogue scale before and after the treatment. The low-level laser illumination decreases significantly and for a longer period the burning sensation. The low-level laser therapy is a valuable alternative for BMS treatment and can be combined with other treatment methods.
Theoretical study of laser-based phototherapies’ improvement via upconverting nanoparticles
Authors: Spyratou E , Kareliotis G , Makropoulou M , Efstathopoulos E , Serafetinides A A 
Published: April 2021

Abstract
The introduction of new upconverting nanoparticles (UPCNPs) in the tumor area is being investigated worldwide as a solution for deep tissue theranostics interventions. Moreover, as the development of biophotonics techniques permits bioimaging in nanoscale, both photodynamic and photothermal sensing should be achieved even at cellular level with minimum perturbation, i.e., in absence of any physical contact between cells and sensing units at a single-cell level via optical tweezers. In our work, we discuss the biophotonic upconversion mechanism of nanoparticles’ excitation/emission at cellular level, under laser trapping conditions, via considering laser radiation of NIR (specifically at λ = 808 nm) for optimal penetration in biological tissues. Moreover, a theoretical simulation model will be presented for evaluation of the electric field distribution in optically trapped particles. Water soluble UPCNPs with maximum absorbance wavelength at λ = 808 nm and emission at 545 nm and 660 nm will be studied. The photoluminescence of biocompatible UPCNPs could provide a promising powerful tool for PDT single-cell analysis and/or for photothermal enhancement and sensing in an optical tweezers’ platform.
Trapping, detection and manipulation of single Rb atoms in an optical dipole trap using a long-focus objective lens
Authors: Beterov I I , Yakshina E A , Tretyakov D B , Entin V M , Singh U , Kudlaev Ya V , Yu Mityanin K , Panov K A , Alyanova N V , Andreeva C , Ryabtsev I I 
Published: April 2021

Abstract
Single alkali-metal atoms in arrays of optical dipole traps represent a quantum register that can be used for quantum computation and simulation based on short-term Rydberg excitations, which switch the interactions between qubits. To load single atoms into optical dipole traps and then detect them by resonance fluorescence, lenses with a large numerical aperture (NA > 0.5) inside a vacuum chamber and expensive EMCCD cameras are commonly used. We present our recent experimental results on demonstrating the trapping of single 87Rb atoms using a long-focus objective lens with a low numerical aperture (NA = 0.172) placed outside the vacuum chamber, and detecting single atoms with a low-cost sCMOS camera. We also present our current results on implementing a single-qubit gate based on optical pumping and subsequent microwave transition between two hyperfine sublevels of a single 87Rb atom with fidelity near 95%.
Propagation of ultra-short dark soliton pulses in an isotropic medium under the influence of third-order linear dispersion and nonlinearity dispersion
Authors: Nenova B , Dakova D , Dakova A , Slavchev V , Kovachev L 
Published: April 2021

Abstract
The nonlinear Schrödinger equation (NSE) is well-known and is one of the most commonly used in the field of nonlinear optics. Pulses with picosecond and femtosecond duration are very well described by the NSE, but it does not work for attosecond and phase-modulated femtosecond laser pulses, where the spectral width of the pulse is of the order of the carrying frequency. In such cases, it is more convenient to use the general nonlinear amplitude equation (NAE). During the propagation of ultra-short pulses in optical fibers, the effects of the third-order linear dispersion and dispersion of nonlinearity become significant and have to be taken into account. We expanded the NAE by including these two effects. In this paper, we present an analytical study on the influence of third-order linear dispersion and dispersion of nonlinearity on the evolution of ultra-short optical pulses and on the possibility of dark soliton formation under such conditions in a medium with normal dispersion.
High-power high-beam-quality sealed-off master oscillator – power amplifier system oscillating in the middle infrared spectral range on strontium atomic transitions
Authors: Kostadinov I K , Yankov G P , Popova L T , Slaveeva S I , Fedchenko Yu I , Temelkov K A 
Published: April 2021

Abstract
High-beam-quality sealed-off master oscillator – power amplifier system is developed and studied based on an atomic strontium vapor laser and delivering high-power laser radiation in the middle infrared spectral range. A diffraction self-filtering of the laser radiation is used to reduce the laser beam divergence to the ultimate diffraction limit. A new optical design is utilized for the master oscillator to visualize the optical path through the entire optical scheme. A large-bore sealed-off laser tube is developed and studied with a stable cavity and is applied as a power amplifier as well. Precise microprocessing of optical grade fused quartz is also performed.
Antibacterial properties of Ta-based ceramic coatings deposited by magnetron sputtering
Authors: Donkov N , Zykova A , Safonov V , Yakovin S , Dudin S , Melnikova G , Petrovskaya A , Kuznetsova T , Chizhik S A 
Published: April 2021

Abstract
Combatting the bacterial infections is an important aspect of any postoperative therapy. Bacterial adhesion to the surface of a biomaterial depends on its properties, such as surface roughness, topography and wettability. The present study analyzes the composition and surface parameters of nanostructured Ta, Ta2O5, TaON coatings and the correlation with their antibacterial properties. The elemental distribution, phase and chemical composition of the coatings were explored by X-ray phase analysis and energy dispersive X-ray spectroscopy. The surface morphology and topography were observed by atomic force microscopy and electron scanning microscopy. The coated surfaces’ advancing contact angles were evaluated by tensiometric measurements. The results of the bacterial viability tests demonstrated the strong bactericidal activity of Ta-based coatings deposited by magnetron sputtering.
Accuracy evaluation of fixed prosthetic constructions made by milling and printing technologies and the influence of temperature changes
Authors: Galeva H , Uzunov T , Sofronov Y , Todorov G 
Published: April 2021

Abstract
The aim of this study is to evaluate the internal and external fit accuracy of fixed metal-ceramic prosthetic constructions made by milling and printing technologies and the influence of temperature changes on this accuracy. An acrylic resin tooth was prepared according to the standard guidelines for a metal-ceramic crown. A standard intraoral silicone impression was taken and a stone model was prepared. The stone model was scanned by an extraoral digital scanner and a digital copy of the prosthetic field was created. The digital copy was used to create a digital prototype of the future metal substructure for the metal-ceramic crown. Using the same data, the metal substructure was formed once by milling technology, and once by 3D-printing technology. The internal surface of both samples was measured. The stone model preparation surface was also measured. All data were compared to the digital prototype. According to the standard technology, a dental technician applied ceramic material, by hand as usual, in layers and the constructions were sintered. After the thermal procedure, once again the substructure’s internal surface was measured and compared with the previous data. The constructions were finished by glazing by the dental technician applying the last layer ceramic and sintering it. The construction’s internal surface was again measured and the data obtained were compared with the previous data. Conclusion about the influence of the temperature changes caused by the sintering process on the metal substructures was made using the data acquired by all the measurements made between the different stages. The difference in the internal fit of the constructions made by the milling and the 3D-printing technology will not affect to crown’s ergonomics. The quality of the internal fit for the construction made by milling technology is better than this made by 3D-printing technology. Unnoticeable changes in the internal surface were found after the temperature changes caused by the process of sintering for both types of constructions. Both types of technologies could be used to produce high quality accurate metal substructures for the needs of the fixed prosthetic dental medicine. The temperature changes caused by the sintering process during the standard metal-ceramic technology have a small influence to the construction’s internal fit.
Effect of Ni and Al substitution on the magnetic properties of Y-type hexaferrite Ba0.5Sr1.5Zn0.5Ni1.5Fe11.92Al0.08O22 powders
Authors: Georgieva B , Kolev S , Krezhov K , Ghelev Ch , Kovacheva D , Tran L-M , Babij M , Zaleski A , Vertruyen B , Closset R , Koutzarova T 
Published: April 2021

Abstract
The effect is reported of substituting the non-magnetic Zn2+ cations with magnetic Ni2+ cations, and of the magnetic Fe3+ cations with non-magnetic Al3+ cations in Ba0.5Sr1.5Zn0.5Ni1.5Fe11.92Al0.08O22 on the resulting magnetic properties. The Y-type hexaferrite powders were synthesized by citric acid sol-gel auto-combustion, followed by appropriate thermal annealing. The saturation magnetization values (Ms
) in a magnetic field of 50 kOe were 36 emu/g and 30 emu/g at 4.2 K and 300 K, respectively. The zero-field-cooled (ZFC) and field-cooled (FC) magnetization vs. temperature (4.2 – 300 K) were measured in dc magnetic fields of 50 Oe, 100 Oe and 500 Oe. The changes resulting from the dissimilar cationic substitutions were identified and discussed.
Research and Application of Intersection Clustering Algorithm Based on PCA Feature Extraction and K-Means
Authors: Lv Wei , Tang Weiyu , Huang Hongliang , Chen Tao 
Published: April 2021

Abstract
Traffic jam and traffic route design are important issues of people’s livelihood. In this paper, machine learning algorithm is used to cluster intersection features. Based on the collected traffic intersection data, PCA dimension reduction technology is used for feature extraction, and then K-Means clustering algorithm is used to sum up the number of entrances, and each intersection is clustered. Thus, a new intersection clustering algorithm is established, studied and applied. The algorithm can match similar intersections, which provides theoretical support for the transportation department and related technical personnel.
Target driven IP Geolocation Algorithm
Authors: Wang Zhanfeng , Niu Yan , Chen Hao , Cheng Guang , Cui Jiawei , Zhang Zhiyi 
Published: April 2021

Abstract
IP Golocation is an important technique to achieve network attack traceability, network security early warning, and improve the ability of cyberspace governance. Due to the limitation of collecting a large number of anchor nodes, it is impossible to accurately infer the IP location to block level or more in a large scale. Therefore, this paper proposes a target driven IP geolocation inference method. Firstly, the candidate anchor node is collected from the subnet or the adjacent subnet of the target IP, then the candidate anchor node is calibrated by their fingerprints, and finally the geolocation of target IP is comprehensively inference by its proximity to anchors. In order to verify the proposed method, 10,000 IPs in Beijing is selected randomly. The experimental results show that the method can effectively infer the geographical location of the target IP address.
Microservice Monitoring and Handoff Algorithm Based on Dual-node Hot Standby
Authors: Zheng Xiaojian , MA Chenzhi 
Published: April 2021

Abstract
The service provider nodes in distributed microservice architecture often exit, join the network or have faults, which will affect the availability of the system. One of the main causes of the problem is the “bump” of service nodes. In this paper, a monitoring and switching algorithm based on dual-node hot backup is adopted, which makes the probability of bumping lower than the traditional single machine and switching method. Moreover, with the gradual increase of system scale, the performance of dual-node hot backup algorithm is still stable. Experimental results show that this method can effectively reduce the occurrence of service consumption node access failure events and improve the availability of the system.
Research on the problems of enterprise internal audit under the background of artificial intelligence
Authors: Zhou Guangxiu 
Published: April 2021

Abstract
With the progress of science and technology and the popularization and development of the Internet, emerging technologies such as big data, intelligence, mobile Internet, cloud computing and blockchain technology have been applied and promoted. Facing the new background, new situation, new changes and new requirements, enterprise internal audit is facing opportunities and challenges. The wide application of artificial intelligence, big data and other technologies can effectively improve the efficiency and quality of internal audit, but also bring many challenges to the development of internal audit. Internal audit should re-examine its own functions, and actively make adjustments in the stages of audit preparation, audit implementation and audit completion, so as to meet the development needs of the new era. This paper expounds the problems faced by enterprise internal audit under the background of artificial intelligence, and puts forward the methods to solve the problems. In order to provide reference for the development of internal audit, and truly realize the value-added role of internal audit for enterprises.
Sand content calculation model based on characteristic analysis of sand-carrying oil flow acoustic signal
Authors: Kai Feng , Kai Wang , Renqi Fu , Jiaxu Chen , Weiping Sun , Wanxiang Lou 
Published: April 2021

Abstract
Aiming at the problem of sand production in oil wells during offshore oilfield exploitation, this paper presents a method for real-time monitoring and acquisition of sand production changes in oil wells. The acoustic signals of the sand-carrying oil flow impactting the inner wall of the pipeline is collected by acoustic sensor installed on the outside of the production pipeline. The characteristics of the signals are analyzed in time and Time-frequency domain to establish a sand content calculation model. The experiment design was based on the indoor simulation of sand production monitoring platform. The objective of this study is to investigate the relationship among the energy of sand-carrying two-phase flow impact acoustic signal, oil flow viscosity, sand particle size, and impact velocity. The characteristics of the acoustic signal in the time-frequency domain system are analyzed by the STFT. The results show that the sand content calculation model can effectively obtain the sand content in the pipeline on the characteristic frequency band of 21.9∼22.1kHz of sand impact acoustic signal. The calculation error of the sand content is no more than 10%. The model can effectively reduce influence of fluid noise on the calculation of sand content. It can accurately monitor the sand content of sand production wells in real time, which provides technical guarantee for safe and efficient production of oil fields.
Granger causal weather time series forecasting simulation combined with mutual information
Authors: Xu Fengkui , Sun Shibao , Zhao Pengcheng , Jia Shaoyong 
Published: April 2021

Abstract
Meteorological science is becoming more and more familiar. The internal driving relationship of weather, timing sequence and its accurate prediction are hot topics in the field of meteorology. This paper proposes a granger weather, timing sequence causal prediction method combining mutual information. In this paper, the information entropy characteristic matrix of the Granger feature set is calculated through mutual information. It while verifying the causal relationship of the weather, timing variables such as temperature, humidity and wind speed, it mines the effective input variables to achieve the purpose of reducing the dimension of time-series data features and improves the prediction accuracy of the target model. Finally, the open source weather data set is used to make a comparative experiment between qualitative and quantitative analysis of the proposed algorithm. The simulation results show that the method is feasible and effective.
A Short-term forecasting model of load demand in summer of Chongqing based on BP neural network
Authors: Zhang Wenzhe , Shi Yan 
Published: April 2021

Abstract
Based on the historical load data collected in July and August 2020 in Chongqing, and in view of the characteristics of the regional load in summer Chongqing, a new short-term load forecasting method was put forward in this paper, which is based on BP neural network and takes into account social activities and meteorological factors. The simulation results show that the proposed short-term load forecasting method can accurately realize the daily maximum load forecasting, it provides a theoretical reference for load forecasting and power resource optimization of smart grid in the future.
Sonar image reconstruction method based on adaptive compensation of very shallow water acoustic channel features
Authors: Li Menglei , Rong Yingjiao , Wang Shirui , Wang Yuchen , Sun Ping 
Published: April 2021

Abstract
Aiming at the problem of eliminating the influence of channel interference on the detection results in the process of using sonar to detect very shallow water targets, a sonar image reconstruction method based on adaptive compensation of very shallow water acoustic channel features is proposed. Standard acoustic source and remote server are used to complete the adaptive calibration process of channel characteristic parameters before detection. The calibrated channel characteristic parameters are used in the subsequent beamforming algorithm to compensate the channel interference. The time-of-flight parameters calculated by the compensation algorithm are used in the subsequent point cloud generation and image reconstruction. Simulation and field test show that the proposed compensation method can improve sonar target detection ability by 25% in very shallow water and complex acoustic channel environment, and the quality of sonar image reconstruction is significantly improved.
Multi-source cross-project software defect prediction based on deep integration
Authors: Zhang Jing , Wang Wei , He Yun , Li Xinfa 
Published: April 2021

Abstract
Cross-project defect prediction (CPDP), training a machine learning model by using training data from other projects, has attracted much attention in recent years. This approach provides a feasible way for small-scale or new developed project with insufficient training data to carry out defect prediction. This paper focus on the bottleneck issue of CPDP, poor accuracy, and propose a deep learning model integration-based approach (MTrADL) for CPDP. This paper consists of two main phases. First, the similarity between target project and source projects is measured by the modified maximum mean discrepancy (MMD) and the top K source projects with high similarity to the target project are selected as training data. Second, for the selected training data, this paper use convolutional neural network (CNN) to build the defect predictor. Each selected training data corresponds to one CNN predictor. Then, multiple predictors are integrated to get the final prediction result. To examine the performance of the proposed approach, this paper conduct experiments on 41 datasets of PROMISE and compare our approach with three state-of-the-art baseline approaches: a training data selection model (TDS), a two-stage transfer learning model (TPTL), and the multi-source transfer learning model (MTrA). The experimental results show that the average F1-score of our approach is 0.76. Across the 41 datasets, on average, MTrADL respectively improves these baseline models by 39.8%, 28.50%, and 10% in terms of F1-score.