bluuebunny/crossref_metadata_2025 huggingface dataset:
A P-type mid-infrared transparent semiconductor LaSe2 film with small hole effective mass and high carrier concentration
Authors: Gao Gang , Tong Lijia , Yang Lei , Sun Chunqiang , Xu Liangge , Xia Fei , Geng Fangjuan , Xue Jingjing , Gong Hao , Zhu Jiaqi
Published: June 2021

P-type transparent conductive materials (TCMs) are urgently needed in the development of photoelectric devices. In particular, the P-type TCMs that can be applied in the mid-infrared range are even rarer due to the conflict between the transparent range and the conductivity of materials. In this work, a P-type mid-infrared transparent conductive LaSe2 film is obtained by a two-step method combining the RF sputtering and a selenized annealing process. The crystal structure of the film has been confirmed by x-ray diffraction and Raman spectrum analysis. According to the Hall effect measurement results, the LaSe2 film has a higher conductivity (about 3.6 S/cm) than that of traditional P-type mid-infrared TCMs, which is attributed to its ten times higher carrier concentration (about 1019 cm−3) and a much smaller hole effective mass (about 0.34 me) compared to the conventional P-type mid-infrared TCMs. The transmittance (about 75%) is at the same level as that of the traditional P-type mid-infrared TCMs. In a sense, the LaSe2 is a promising candidate material for the development of mid-infrared photoelectric devices.
Giant volume magnetostriction in La0.85Ce0.15Fe12B6
Authors: Diop L. V. B. , Amara M. , Isnard O.
Published: June 2021

We report the discovery of giant magnetostriction and huge negative thermal expansion (NTE) in the itinerant-electron metamagnetic compound La0.85Ce0.15Fe12B6. This system presents multiple magnetic transformations, antiferromagnetic–ferromagnetic (AFM–FM) and ferromagnetic–paramagnetic (FM–PM), driven by changes in both external field and temperature. The magnetic-field–dependent magnetostriction exhibits irreversible abrupt jumps at T ≤ 5 K, while it evolves smoothly with applied field above 5 K. A giant positive volume magnetostriction of ΔV/V (20 K, 6 T) = 0.80% is observed across the field-induced first-order AFM–FM metamagnetic transition. It is further revealed that the FM–PM transition is accompanied by a remarkably large NTE with a coefficient of linear thermal expansion αL = −34 × 10−6 K−1 over a temperature window of ΔT ∼ 63 K.
Preparing for subsea source control response and optimising timelines – IOGP Reports 592 and 594
Authors: Best Andrew , Brenan Patrick
Published: June 2021

In response to the Montara and Macondo subsea well incidents in 2009–10, the industry’s ability to respond to a subsea source control (SSC) event has greatly improved. Industry invested in response capabilities, and established best practices to resolve future potential offshore incidents. The investment has advanced science, engineering, and equipment developments, establishing a higher standard of preparedness and capability. The industry now has a high confidence in its ability to deal with a subsea well release. This rapid growth in capability has led to variations in equipment and response plans, resulting in elevated complexity within an already highly technical field. To simplify SSC response plans, common understanding and consistency is required. With a common understanding of the response plan comes enhanced industry, regulator, and community confidence in the ability of the energy industry to appropriately manage its environmental and social impacts. The IOGP Report 594 Source Control Emergency Response Planning Guide for Subsea Wells is one of the available simplification resources. Another is the joint IOGP and NOPSEMA Report 592 Subsea Capping Response Time Model Toolkit User Guide and tools, which map the response plan linking dependencies between all the actions and the critical path items that influence response time: both were published in 2019. This peer-reviewed paper describes these efforts and shares their content. It aims to highlight the available resources, promote a common standardised approach, and share how workshops are supporting implementation. In doing so, a standard of recognised best practices in planning and engineering requirements is communicated.
Net zero 2020
Authors: MacDougall Iain , Glade-Wright Ollie , Gove Bindi , Berkinshaw Todd
Published: June 2021

Cooper Energy recognises the challenge of climate change, the goals of the Paris Agreement and the role of both energy companies and society in reducing greenhouse gas emissions, given the proportion of emissions generated from energy production and consumption. In 2020, Cooper Energy became Australia’s first carbon neutral domestic gas company. We fully offset our fiscal year 2020 Scope 1 (direct), Scope 2 (indirect) and controllable Scope 3 (business travel and embedded energy) greenhouse gas emissions. The company was recognised for this achievement with the award of the 2020 South Australian Premier’s Award for Environment. We plan to offset our carbon emissions annually, recognising the long-term benefits to our business, the environment and the communities where we operate. To achieve net zero carbon emissions in 2020, Cooper Energy partnered with Greening Australia’s Biodiverse Carbon and invested in the Morella Biodiversity project, at the eastern end of the Coorong in south-east South Australia. The partnership also covers the early conceptual stages to progress a similar project in Victoria near to our Gippsland and Otway operations. This paper expands on the strategy, challenges, risks, opportunities and co-benefits of taking a forward-looking position in this area, which is aligned with The Cooper Energy Values and the direction of the broader community. This includes the decision to favour investment in appropriate high quality domestic projects near to our operational activities over lower cost international projects or simply purchasing offset credits on a carbon market. The paper explores how our net zero commitment will act as a driver to reduce emissions intensity in our operations and add value for Cooper Energy stakeholders.
Genetic variability of seed yield and oil nutritional attributes in linseed dominated by biennial variation
Authors: Ataii Ehsan , Mirlohi Aghafakhr , Sabzalian Mohammad R. , Goli Sayed Amir Hossein , Sadri Nafiseh , Sharif-Moghaddam Negar , Gheysari Mahdi
Published: June 2021

Improving seed yield and oil quality of oilseed crops can aid in provision of a nutritious diet for humans. A worldwide collection of linseed was evaluated for seed yield (YLD), seed oil (OIL) and protein content (PRO), oil fatty acid composition, omega-3 to omega-6 ratio (ω3/ω6), total tocopherol content (TTC), and total phenolic content (TPC). At 2 years, higher temperature (~7%) and lower relative humidity (~16.6%) during the seed filling and maturity period (dryer condition) were correlated with significant decreases in YLD (~18%) and OIL (~4.5%), lower contents of linolenic acid (~13%) and TTC (9.8%), and lower ω3/ω6 ratio (~31%); oleic (~9%) and linoleic acid contents (~23%) and TPC (14.4%) increased. Correlation results demonstrated some significant associations among quantitative traits such as YLD, OIL, and thousand seed weight (TSW); however, the association of these traits with qualitative indices was mostly negative. Genotypes were classified irrespective of their geographical origin and independent of seed or flower colour. In this classification, a yellow-seeded Canadian group had the lowest ω3/ω6 ratio (~0.05), the highest seed yield and high TTC, whereas groups with the highest ω3/ω6 ratio (>3.0) had the lowest oil TTC and low to average seed yield. Results suggested that some brown-seeded Asian genotypes with high grain yield and oil potential, higher ω3/ω6 ratio, and other more stable oil quality indices are suitable to develop broadly adaptive varieties under the possible fluctuation of climatic factors. Other genetic groups could also be used for breeding programs with specific objectives.
Mass-immigration determines the assembly of activated sludge microbial communities
Authors: Dottorini Giulia , Michaelsen Thomas Yssing , Kucheryavskiy Sergey , Andersen Kasper Skytte , Kristensen Jannie Munk , Peces Miriam , Wagner Dorottya Sarolta , Nierychlo Marta , Nielsen Per Halkjær
Published: June 2021

Significance

Wastewater treatment plants are engineering technologies used worldwide to protect the environment and human health. Microbial communities sustain these plants, so it is crucial to know the key factors responsible for the community assembly. We show, in contrast to existing understanding, that microbial immigration largely controls the community structure in these plants and that the fate (growth or death) of immigrating species in the plants is controlled by local factors. The community structure was quantitatively predicted by the immigrating microbial community, highlighting the need to revise the way we today understand, design, and manage microbial communities in wastewater treatment plants.
Deep representation learning improves prediction of LacI-mediated transcriptional repression
Authors: Garruss Alexander S. , Collins Katherine M. , Church George M.
Published: June 2021

Significance

The understanding of protein function increases with new experimental and evolutionary datasets. A major challenge is to apply machine learning to these datasets to capture essential features of protein function. Here, we analyze the experimentally determined repression function for tens of thousands of mutants of the LacI protein. This study provides a continuous, noncategorical repression value across a majority of all single mutations and for thousands of higher-order mutations. To develop a top-performing model for the prediction of repression by LacI, we compare several leading variant effect prediction algorithms. A deep representation learning paradigm, first trained across millions of proteins from all known protein families and then fine-tuned using LacI experimental data, offers the highest predictive performance of repression function.
Alternative splicing of GluN1 gates glycine site–dependent nonionotropic signaling by NMDAR receptors
Authors: Li Hongbin , Rajani Vishaal , Han Lu , Chung Danielle , Cooke James E. , Sengar Ameet S. , Salter Michael W.
Published: June 2021

Significance

N
-methyl-D-aspartate receptors (NMDARs), which are critical in the brain, are increasingly being shown to signal without ion flux (i.e., “metabotropically”). What controls the metabotropic function of NMDARs is unknown. We discovered that a form of metabotropic signaling—glycine priming—is controlled by alternative splicing of the mRNA encoding one NMDAR subunit, GluN1. Our discovery was surprising because the spliced exon encodes a peptide cassette in the extracellular region of GluN1 far from the plasma membrane, and yet, metabotropic function requires signaling across the neuronal membrane. Moreover, we found that this metabotropic function of NMDARs is neuron cell–type specific: excitatory neurons show glycine priming, whereas inhibitory neurons do not. These findings have widespread implications for NMDARs in health and disease.
Audit Forum #1: Preparing For Remote GMP and GDP Audits
Authors: Moldenhauer Jeanne
Published: June 2021

Since the beginning of the Covid-19 pandemic, business life has changed. There is a reluctance to travel. Companies are reluctant to have visitors on site. There has been a significant increase in employees working from home have also been increases in having meetings held virtually. This has resulted in a significant reduction in company audits by customers and regulatory agencies. As such, many new issues have arisen in both how these audits are conducted for both good manufacturing practices and good distribution practices audits. This paper discusses some of these issues.
Neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) in Ménière’s disease and vestibular neuritis
Authors: Quaranta Nicola A.A. , Salzo Anna E. , Pontillo Vito , Scarano Emanuele , Sergi Bruno , Picciotti Pasqualina M.
Published: June 2021

Objective

several hypothesis including viral infection, vascular disturbance, and immune-mediated mechanisms have been proposed in Menière disease (MD) and vestibular neuritis (VN) and the role of inflammation has been also investigated. To evaluate the role of neutrophil to lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR) and metabolic parameters in MD and VN patients.

Methods

we retrospectively studied 120 subjects (40 affected by MD, 40 by VN and 40 normal controls). We analyzed glycaemia, Haematocrit Blood Test (HCT), leukocytes, neutrophils, lymphocytes, platelets, cholesterol, prothrombin time and the related international normalized ratio (PT-INR), fibrinogen, erythrocyte sedimentation rate (ESR), NLR and PLR.

Results

Neutrophils, leukocytes, cholesterol, ESR, NLR and PLR values of MD patients are significantly higher than normal controls. Higher significant values are reported for glycaemia, neutrophils, lymphocytes, leucocyte, fibrinogen, ESR, NLR and PLR in VN patients compared to NC.

Conclusions

High levels of NLR and PLR indicate the presence of an acute inflammatory state in both MD and VN. Our data confirm the role of proinflammatory state leading to microvascular injury together with risk factors for atherogenesis.
Key comparison BIPM.RI(I)-K4 of the absorbed dose to water standards of the ARPANSA, Australia and the BIPM in 60Co gamma radiation
Authors: Kessler C , Burns D , Oliver C , Bailey T , Harty P , Butler D
Published: June 2021

Main text

A new key comparison of the standards for absorbed dose to water of the Australian Radiation Protection and Nuclear Safety Agency (ARPANSA), Australia and the Bureau International des Poids et Mesures (BIPM) was carried out in the 60Co radiation beam of the BIPM in November 2020. The comparison result, based on the calibration coefficients for two transfer chambers and evaluated as a ratio of the ARPANSA and the BIPM standards for absorbed dose to water, is 0.9995 with a combined standard uncertainty of 5.1 parts in 103. The result agrees within the uncertainties with the comparison carried out in 2010. The results are analysed and presented in terms of degrees of equivalence, suitable for entry in the BIPM key comparison database.

To reach the main text of this paper, click on Final Report. Note that this text is that which appears in Appendix B of the BIPM key comparison database https://www.bipm.org/kcdb/.

The final report has been peer-reviewed and approved for publication by the CCRI, according to the provisions of the CIPM Mutual Recognition Arrangement (CIPM MRA).
Levitation, oscillations, and wave propagation in a stratified fluid
Authors: Carpineti Marina , Croccolo Fabrizio , Vailati Alberto
Published: June 2021

We present an engaging levitation experiment that students can perform at home or in a simple laboratory using everyday objects. A cork, modified to be slightly denser than water, is placed in a jug containing tap water and coarse kitchen salt delivered at the bottom without stirring. The salt gradually diffuses and determines a stable density stratification of water, the bottom layers being denser than the top ones. During the dissolution of salt, the cork slowly rises at an increasing height, where at any instant its density is balanced by that of the surrounding water. If the cork is gently pushed off its temporary equilibrium position, it experiences a restoring force and starts to oscillate. Students can perform many different measurements of the phenomena involved and tackle non-trivial physical issues related to the behaviour of a macroscopic body immersed in a stratified fluid. Despite its simplicity, this experiment allows to introduce various theoretical concepts of relevance for the physics of the atmosphere and stars and offers students the opportunity of getting acquainted with a simple system that can serve as a model to understand complex phenomena such as oscillations at the Brunt–Väisälä frequency and the propagation of internal gravity waves in a stratified medium.
Linear multi-photon storage based on dark modes with frequency tuning
Authors: Xu Shuang , Gong Wei-Jiang , Shen H Z , Yi X X
Published: June 2021

We propose a quantum memory applicable to the optical regime based on a linear system. The system is in a symmetrical star configuration: one central mode is both connected to the input–output channel and uniformly coupled to a number of modes with tunable frequencies. We show that, as long as the number of these tunable modes is double an odd number, such a configuration is just flexible enough to perform the storage and on-demand recall of a number of individual photons. Tuning of the mode frequencies is feasible experimentally by means of adiabatic frequency tuning, and we show the system is scalable and robust against various type of imperfections. Moreover, the linearity of the system is compatible with the use of single-mode continuous-variable error correction code. Our results therefore provide a promising approach to the storage of many photons carrying protected quantum information.
Gravitational-wave cosmological distances in scalar-tensor theories of gravity
Authors: Tasinato Gianmassimo , Garoffolo Alice , Bertacca Daniele , Matarrese Sabino
Published: June 2021

We analyze the propagation of high-frequency gravitational waves (GW) in scalar-tensor theories of gravity, with the aim of examining properties of cosmological distances as inferred from GW measurements. By using symmetry principles, we first determine the most general structure of the GW linearized equations and of the GW energy momentum tensor, assuming that GW move with the speed of light. Modified gravity effects are encoded in a small number of parameters, and we study the conditions for ensuring graviton number conservation in our covariant set-up. We then apply our general findings to the case of GW propagating through a perturbed cosmological space-time, deriving the expressions for the GW luminosity distance dL
(GW) and the GW angular distance dA
(GW). We prove for the first time the validity of Etherington reciprocity law dL
(GW) = (1+z)2 dA
(GW) for a perturbed universe within a scalar-tensor framework. We find that besides
the GW luminosity distance, also the GW angular distance can be modified with respect to General Relativity. We discuss implications of this result for gravitational lensing, focussing on time-delays of lensed GW and lensed photons emitted simultaneously during a multimessenger event. We explicitly show how
modified gravity effects compensate between different coefficients in the GW time-delay formula: lensed GW arrive at the same time as their lensed electromagnetic counterparts, in agreement with causality constraints.
Beyond perturbation theory in inflation
Authors: Celoria Marco , Creminelli Paolo , Tambalo Giovanni , Yingcharoenrat Vicharit
Published: June 2021

Inflationary perturbations are approximately Gaussian and deviations from Gaussianity are usually calculated using in-in perturbation theory. This method, however, fails for unlikely events on the tail of the probability distribution: in this regime non-Gaussianities are important and perturbation theory breaks down for |ζ| ≳ |f
NL|-1. In this paper we show that this regime is amenable to a semiclassical treatment, ħ → 0. In this limit the wavefunction of the Universe can be calculated in saddle-point, corresponding to a resummation of all the tree-level Witten diagrams. The saddle can be found by solving numerically the classical (Euclidean) non-linear equations of motion, with prescribed boundary conditions. We apply these ideas to a model with an inflaton self-interaction ∝λζ̇4. Numerical and analytical methods show that the tail of the probability distribution of ζ goes as exp(-λ-1/4ζ3/2), with a clear non-perturbative dependence on the coupling. Our results are relevant for the calculation of the abundance of primordial black holes.
A test of cosmic distance duality relation using SPT-SZ galaxy clusters, Type Ia supernovae, and cosmic chronometers
Authors: Bora Kamal , Desai Shantanu
Published: June 2021

We carry out a test of the cosmic distance duality relation using a sample of 52 SPT-SZ clusters, along with X-ray measurements from XMM-Newton. To carry out this test, we need an estimate of the luminosity distance (DL) at the redshift of the cluster. For this purpose, we use three independent methods: directly using DL from the closest Type Ia Supernovae from the Union 2.1 sample, non-parametric reconstruction of DL using the same Union 2.1 sample, and finally using H(z) measurements from cosmic chronometers and reconstructing DL using Gaussian Process regression. We use four different functions to characterize the deviations from CDDR. All our results for these (4 × 3) analyses are consistent with CDDR to within 1σ.
Some Mechanical and Physical Studies of Granitic Rocks in Um Taghir, Eastern Desert, Egypt
Authors: Awad H A M , Nastavkin A V
Published: June 2021

Granitic rock is considered one of the most important economic materials used as building materials, ornamental stones, and other purposes. According to previous radiological studies conducted on these granites, it was found that the activity concentrations of 238U, 232 Th and 40 K of these granitic rocks are natural as well as the radiation effects are not harmful due to the natural radioactivity of the examined granites so that it can be exploited economically in the future.The current study aims to determine some of the physical and mechanical properties of granites in the Um Taghir area to detect these rocks’ suitability for ornamental stones. The samples of the granitic rocks were cut according to the American Society for Testing and Materials specifications (cubic shape) for the detection of uniaxial compressive strength in addition to some of the physical properties were determined for each sample. Granite rock samples showed good results according to mechanical and physical tests. So that it can be extracted, transported and later used for various economic purposes.
Invariant Procedure for Error Sensitivity Analysis Applied to Cyclic Creep Modelling
Authors: Kaygorodtseva A A , Zakharchenko K V , Kapustin V I , Shutov A V
Published: June 2021

Cyclic creep, also known as ratcheting, is a progressive accumulation of inelastic strain under cyclic stress-controlled loading. This mechanical effect is of great importance for numerous applications. In engineering practice, phenomenological models of cyclic creep are calibrated against a limited set of macroscopic test data. Since the testing results are prone to systematic and non-systematic experimental errors, the impact of experimental errors on the quality of simulation has to be analysed. A simple inspection procedure is demonstrated and tested. Based on the Monte Carlo computations, it allows for analysis of error propagation through the simulation cycle. The focus of the paper is on the independence of the procedure from the chosen model parametrization. For demonstration purposes, cyclic creep of VT6 alloy is simulated. The corresponding macroscopic constitutive equations are based on the second Ohno-Wang model, combined with refined rule of isotropic hardening. Two different parametrizations are introduced to show that the procedure predicts the same results for both of them.
Analysis of Residual Stress Distribution in Rods after Drawing Process with Regard to Process Variables
Authors: Kuznetsova E V , Kolmogorov G L , Evsina A V
Published: June 2021

Currently, many researchers pay attention to studying the influence of process variables on the quality of metal products after manufacture. The most common methods of metalworking are forming processes, in which a high degree of deformation, uneven plastic deformation, and elevated temperatures are utilized. In most cases of manufacturing using these methods, a self-balanced system of residual stresses is formed that significantly affects the accuracy, strength, durability, reliability, corrosion resistance, and fatigue strength of machine parts after manufacture and processing. At the same time, the level of technological residual stresses depends on the main process variables. And in this regard, the analysis of the residual stress calculation for the deformation of rods will identify the effect of process variables, mechanical properties of the material, the geometry of the workpiece on the level and distribution of formed residual stresses. The object of the study is distributions of residual stresses formed after plastic deformation in rods and wire. In the work, experimental data on the distribution of residual stresses in rods after drawing were investigated. The residual stress calculation method takes into account parameters of technology, geometry and mechanical constants of material. Dependencies of axial and circumferential residual stresses in steel rods and wires after drawing were found.
Vertical Density Inhomogeneity of Kama Reservoir Water Masses in the Region of Berezniki: Possible Genesis and Influence on the Stability of Water Use
Authors: Lepikhin A P , Lyubimova T P , Bogomolov A V , Lyakhin Yu S , Tiunov A A , Yu Kolchanov V , Parshakova Ya N
Published: June 2021

The stability of water supply systems is one of the main factors that determine the reliability of the functioning of large industrial complexes. This problem is considered on the example of the “Azot” branch of URALCHEM JSC in the city of Berezniki, which takes fresh industrial water from the Kama river (Kama reservoir). A specific feature of this water body is the significant variability of its hydrological regime. During the summer dry season, it is characterized by low flow velocities. In winter, with a decrease in the water level in the reservoir, a typical river regime is observed. In addition, there is a strong technogenic impact on the water body. The impact is formed largely due to non-declared dispersed (diffuse) sources. Their characteristic feature is high mineralization and, accordingly, the density of the formed wastewater. Their behavior is fundamentally different from the processes of dilution and migration of effluents with neutral buoyancy. A two-layer structure is formed, when the content of the main ions in the surface horizon is more than an order of magnitude less than in the bottom layer. This circumstance must be taken into account when assessing the reliability of the functioning of water intakes. The most effective tool for solving such problems is the conjugation of a complex of field monitoring observations with computational experiments using hydrodynamic models in one-, two- and three-dimensional formulations.
Double-Diffusive Convection in the Continuous Flow Microreactors
Authors: Mizev A I , Mosheva E A , Shmyrov A V
Published: June 2021

In this paper, the mixing process of two solutions of inorganic salts in a continuous flow channel with Y-type micromixer is investigated. Due to different diffusivity rates of solutes the double-diffusion convection develops in the channel. To visualize convective flows and the distribution of mixing substances the shear interferometer technique and a fluorescent dye are used. The latter makes it possible to quantify the mixing degree. The mixing extent for different volume flow rates is calculated. The comparison of convection and pure diffusion mechanisms of mixing is provided.
Capillary Wave-Detection Algorithm Based on Cylindrical Solitary Waves
Authors: Mizeva I
Published: June 2021

In multiphase systems the thermodynamic and rheological properties of the interfacial layer have influences on the overall system behavior. The geometrical properties of capillary waves are extremely useful in the characterization of surface parameters. In Shmyrov et al 2019, the modified capillary wave technique was successfully used to perform experiments, to register surface profiles and to realize data processing, yet the algorithm for semi-manual data processing proposed by the authors is labor-intensive and time-consuming. It appears that the analysis of the data is compex because of specific geometry problems, presence of noise at different scales, and data gaps. In this study, the algorithm for analysis of a surface instantaneous profiles formed due to capillary waves propogating is proposed. It was found that the noise and the useful signal have different scales. Moreover, the structure of the useful signal is defined, and therefore it becomes possible to study the noise part of the signal and the patterns of the useful signals. On the basis of the preliminary knowledge about the signal structure, the algorithm has been developed to overcome the above mentioned problems. The proposed method has been tested on the set of semi-synthetic data and provides a reliable result.
Influence of Thermal Limiters on the Formation of the Dendritic Structure of the Welded Stainless Steel Layer
Authors: Chinakhov D A , Akimov K O , Dubrovskiy A S , Ilyaschenko D P
Published: June 2021

In the work the influence of thermal limiters on the formation of a dendritic structure of the stainless steel AISI 304L layer deposited by electric arc welding in argon medium was investigated. The structure of the billets was investigated in the mode of differential interference contrast. The analysis of the obtained structures showed that the use of thermal limiters in the form of graphite skids allows to obtain a uniform structure in billets without sharp transitions between the deposited layers.
Study on the Resonant Torsion Vibration in Hourglass Specimens under VHCF Loading
Authors: Nikitin I S , Nikitin A D , Stratula B A
Published: June 2021

The problem of cyclic loading under pure torsion is an important problem for numerous different industrial applications, such as shafts, springs, blades, and others. The loading conditions for aircraft, railway, automobile industries are often corresponding to long fatigue life. The rough estimation shows that the number of cycles for springs in car engine is exceeds 108 cycle while blades for aircraft turbine may undergo more than 1010 loading cycles. Such, to provide a safety in service life for such elements a multiaxial fatigue failure criterion is needed to predict damage zone location and fatigue life. This paper is aimed to introduce the multi regime approach to predict fatigue damage zone evaluation and number of cycles to crack initiation and total fatigue life. The presented approach is based on damage theory supplemented by multiaxial failure criterion. The proposed model includes the algorithm for automatic determination the fatigue loading range (low-, high- or very-high cycle fatigue) and allows different crack opening modes. To show how to apply the proposed approach and verify the results of calculation the series of numerical simulation on hourglass specimen subjected to VHCF pure torsion is performed. The results of numerical simulation are compared to VHCF torsion tests.
Stochastic Modeling of Protein Field with a Delayed Feedback
Authors: Bratsun D A , Buzmakov M D
Published: June 2021

Protein fields synthesized by genes play a principal role in the functioning of living systems. The processes of gene regulation determine the properties of these fields. Since the number of nucleotides usually is not large, a deterministic description of the field dynamics is insufficient. In this work, we consider a special kind of protein field, the dynamic behavior of which is described by the non-Markov process. Generally, the dynamics of complex organic compounds is time-dependent and spatially extended, and it may depend on all the previous evolution of the system. We consider a time-delayed repressilator as a model system. We study this system numerically using a modified Gillespie algorithm. New dynamic phenomena, which are visible only within a stochastic description, are reported. We show that synchronization in a gene expression occurs much faster due to the non-linear interaction of noise and delay. It results in almost regular oscillations even below the neutral curve derived within the deterministic analysis. We apply a hybrid approach to study the spatial dynamics of the repressilator proteins. This approach includes a deterministic calculation of the diffusion fluxes between cells and the stochastic simulation of gene regulation processes. We found that the combined action of time-delay, noise, and spatial signaling can lead to pattern formation even when the deterministic description predicts the absolute stability of the system.
On the Origin of Geostrophic Liquid Cylinders in Rotating Sphere with Oscillating Inner Core
Authors: Subbotin S
Published: June 2021

The effect of non-axisymmetric inertial waves on the zonal flow structure in a rotating spherical shell is studied experimentally. The wave source is the inner core, which performs circular oscillations in the equatorial plane. The case of positive frequencies that corresponds to the advanced core motion is considered. As a result of non-linear effects, a quasi-two-dimensional axisymmetric steady flow with a complex distribution of angular velocity is generated. The extrema in the velocity profile are equivalent to the nested liquid geostrophic cylinders, which appearance is due to the interaction of the inertial waves within a viscous boundary layer. One of the extrema is associated with the critical latitude at the core boundary, where the inertial waves are excited. With an increase in the oscillation frequency, the position of this extremum gradually shifts to the rotation axis. Additional geostrophic circulation occurs close to the points where the inertial wave reflects from the cavity boundary.
Plasma Treatment of Vascular Implant
Authors: Chudinov V S , Shardakov I N , Litvinov V V , Galkin S V , Kondyurin A V
Published: June 2021

This paper examines a carbon layer on a blood vessel implant. The carbon layer is created by high energy ions bombarding an inner surface of the polyurethane implant. An analysis of the molecular structure of the layer was carried out, demonstrating the appearance of free radicals stabilized by aromatic clusters, as well as new carbon-carbon, oxygen-containing and nitrogen-containing groups in the inner surface of the blood vessel implant. The covalent adsorption of the protein on the carbon layer inside the implant has been proven. The antithrombogenicity of the carbon layer with a covalently bound protein on polyurethane implant of blood vessels in an experiment on rabbits has been shown.
A monocular vision positioning method based on topology pattern of artificial landmark
Authors: Gu Yang , Zhong Weibo , Chen Ruiyu
Published: June 2021

Image-based positioning accuracy is usually affected by image rotation and/or distortion due to the changes of the sensor orientation. In this paper, the artificial landmark is composed of color block with different shapes, and its topology pattern is composed of the number of the block shapes, colors, shape and color of each block and topological relation among the blocks, which are robust for the artificial landmark rotation and/or tilting. The positioning is based on artificial landmark pattern matching and the corresponding relation between artificial landmark and its position. In our experiments, 196 different artificial landmarks are layered on the 3 × 3M plane uniformly. There are four blocks in an artificial landmark and each block has six different shapes and four different colors. The experiment results show that the attributions of the block were calculated accurately, the topology pattern construction and recognition method for the artificial landmark are feasible, reliable and can be used in monocular vision positioning.
Research on Image Super-resolution Technology Based on Sparse Constraint SegNet Network
Authors: Lin Ruikai , Wang Liyuan , Xia Tao
Published: June 2021

Aiming at the problems of long time-consuming and low accuracy in extracting buildings with traditional machine learning methods. In this paper, the SegNet semantic segmentation models on deep learning is used to improve the algorithm, and a high-resolution remote sensing image building extraction algorithm based on sparse constrained SegNet are proposed. First, regular terms and Dropout are added to the SegNet model, which greatly reduces the occurrence of model over-fitting; secondly, in order to extract richer semantic features for the model, the algorithm introduces a pyramid pooling module; finally, the Lorentz function sparse constraint factor is introduced to the SPNet model, Construct a new semantic segmentation model LSPNet. In order to verify the reliability and applicability of the proposed algorithm, the optimized LSPNet model is used to identify and extract the buildings in the high-resolution data set. Experimental results show that compared with traditional machine learning methods, this method has the advantages of fast convergence and high accuracy, and has a good application prospect.
High-Precision Indoor Robot Dynamic Obstacle Detection with Laser and Camera
Authors: Hu Chuanqi
Published: June 2021

Indoor robot is a very common robot, and its main navigation method is laser SLAM. In the process of detecting dynamic obstacles with laser SLAM, the clustering effect is not obvious, the accuracy is low, and the real-time performance is poor. To solve this problem, a sensor fusion method of lidar and monocular camera is proposed, which improves the accuracy of detecting the position of moving obstacles. When processing lidar data, first preprocess the data, then use the BDSCAN algorithm to cluster the point cloud, and finally use the Kalman filter to predict and calculate the location of the moving obstacle. When processing the data of the monocular camera, the YOLOv3 algorithm is used to quickly detect the target and return the position of the monocular camera. After obtaining the camera and laser data, according to the installation position of the radar and camera, map the position calculated by the radar to the coordinates of the camera. If the coordinate difference after mapping is small, it can be considered that the two sensors have detected the same target. The result is returned to the display interface. Using this method, the efficiency and accuracy of indoor robots in detecting moving obstacles have been greatly improved.
Research on Computer Image Processing Technology in Navigation and Navigation
Authors: Ke Jinding
Published: June 2021

In view of the existing navigation systems used on ships, the Baidoo satellite signal access recognition rate is low, and the target recognition accuracy is poor. The paper proposes a computer image recognition method for the positioning target of the ship navigation system based on the Baidoo satellite. In view of the large resource consumption and low calculation rate of the traditional method in the calculation process of the Baidoo satellite signal, the compressed sensing image processing algorithm of single-layer wavelet transform is introduced to perform directional exclusive calculation on the Baidoo satellite signal. The research in the thesis found that the Baidoo satellite ship navigation system positioning target accurate recognition method based on the single-layer wavelet transform-based compressed sensing image processing algorithm can quickly, effectively and accurately lock and identify the set target in the Baidoo satellite navigation.
Mathematical Analysis of the Inhibitory Effects of Ten Kinds of Fungicides Applied on Apple
Authors: Liu Wenyu , Han Lin , Chi Wenjuan
Published: June 2021

Apple ring rot is one of the three major diseases of apple, which seriously affects the yield and quality of apple. At present, chemical agents are mainly used to prevent and control apple ring rot. In this study, 10 kinds of low virulence fungicides were selected. The inhibitory effects of 10 kinds of fungicides on Botryosphaeria dothidea were determined. The results indicated that 50% carbendazim and 70% thiophanate methyl had the best mycelial growth inhibition effect among 10 kinds of fungicides. The inhibitory effect of 50% carbendazim on hyphae was 91.63% under the concentration of 400 times dilution, the inhibitory effect of 70% thiophanate methyl on hyphae was 90.31% under the concentration of 500 times dilution, and there were recommended to use.
Research on High Resolution Optical Remote Sensing Image Technology Based on Internet Architecture
Authors: Xiao Gengyi
Published: June 2021

Target detection technology in high-resolution optical remote sensing images is of great significance in both civil and military fields. Based on the Internet architecture, this paper proposes a multi-class target detection method for high-resolution and high-resolution optical remote sensing images. The fused multi-layer features are used for detection. In view of the challenges of complex background and deformation of the target, the deformable convolution network can be used for reference to extract the characteristics of the target itself and reduce the background interference In order to reduce the storage space required by the deep convolution neural network model and increase the portability of the network, I also put forward a method of lightening the network. Experiments show that our proposed method is feasible. Compared with the popular target detection method based on deep convolution neural network, our method has great advantages in precision and recall rate.
Study on cyclic voltammetric electrochemical fingerprint method for origin traceability of rice
Authors: Sha Min , Tang Zhilong , Zhang Ding , Zhang Zhengyong , Liu Jun
Published: June 2021

The origin traceability of geographical indication rice has always been highly concerned, this paper focused on the perspective of non-equilibrium samples, and the feasibility of using the cyclic voltammetric electrochemical fingerprint of rice to identify the origin of rice was studied. Jiansanjiang, Fangzheng and Xiangshui rice, whose production places were close, were selected, and the fingerprint collection method and data preprocessing method were explored respectively. Fingerprints with rich information, significant features were obtained by fast detection. Principal component analysis combined with support vector machine analysis were used to establish the discrimination model, the recognition accuracy of the prediction set was over 90.0%, showing a good application prospect. The electrochemical fingerprint of the non-equilibrium sample measured by real-time tracking of the reaction process could not only reflect the differences in the types and contents of the sample components, but also show the differences in the chemical properties of the components, providing a new idea for easy and accurate identification of food.
Image de-blurring Model based on Machine Learning
Authors: Li Junsheng , Xu Silu , Wang Cong
Published: June 2021

Due to the influence of haze in winter, outdoor images usually lose contrast and fidelity. In view of the fact that most de-fog algorithms are not effective for images with large sky areas, an improved dark channel a priori de-fog method is proposed. First of all, the sky region is segmented according to the image gradient information, and on the basis of sky segmentation, the atmospheric light value is reasonably estimated by setting the discriminant formula combined with the high brightness and smoothness of atmospheric light reference pixels. Secondly, according to the different dark channel values, the piecewise linear function is used to dynamically modify the adjustable parameters to solve the local shadow caused by excessive defog. Then, the transmittance estimated by the bright channel model and the improved dark channel prior model are fused, and the edge is optimized by guided filtering. Finally, combined with the atmospheric scattering model, the defog image is obtained by brightness compensation and contrast stretching. The experimental results show that the improved method can effectively improve the image distortion, enhance the image contrast and details, especially in maintaining the visual authenticity of the sky region.
Detection of Fruit Surface Defects Based on Machine Vision
Authors: Cao Yayue
Published: June 2021

With the continuous improvement of social level, the perfection of fresh fruit surface has become a potential requirement for people to purchase. Aiming at the problems of high intensity and low efficiency in manual inspection, a method combining computer machine vision technology with MATLAB application was designed to detect the surface defects of fruits. Experiments show that this method has advantages in speed and precision in detecting fruit surface, and has certain application value.
Optimization of Drone Quantity Based on Empirical Analysis in Bushfire Extinguishment
Authors: Zhou Zilong , Lin Fu , Gong Xinyi
Published: June 2021

With the deterioration in the environment, extreme weather is more likely to occur. The wildfire is becoming severer in turns of frequency and magnitude, causing disastrous damage to our fragile ecosystem. In this paper, we purpose a model to identify the optimal number of drones in case of any potential threat posed by bushfire in Victoria, Australia. In this paper, we use satellite data from space agencies such as NASA and the European Space Agency to determine the initial conditions and parameters of the model. including land cover, topography, traffic development, potential reinforcements nearby, distance to water and historical wildfires. We extract the data of several modes and determine the coefficients that affect the forest-mass. According to our simulation results, the optimal expected number of SSA UAV and relay UAV is 53 and 85 respectively.
Survey of Target Detection Based on Neural Network
Authors: Deng Bao , Lv Hao
Published: June 2021

Target detection is a hot topic in the field of artificial intelligence, which is widely used in robot, UAV, aerospace and other fields. In this paper, the research background and significance of target detection are summarized, and two categories of target detection algorithms based on deep learning, i.e., candidate region based and regression based, are described. For the first category, a series of region with convolutional neural network (r-cnn) algorithms are introduced, this paper introduces the researchers’ research on the basis of r-cnn algorithm: the improvement of feature extraction network, pooling layer of region of interest and non-maximum suppression algorithm. The second algorithm is divided into Yolo (you only look once) series, SSD (single shot multibox detector) algorithm and its improvement. According to the current target detection algorithm in the development of more efficient and reasonable development trend, the research hotspot of target detection algorithm in the future is prospected, including unsupervised and unknown class object detection.
Online Machine Learning System of Power Quality Information Technology Based on Big Data
Authors: Wang Wei
Published: June 2021

Power quality monitoring has the characteristics of large amount of collected data and high collection frequency. Long-term monitoring will form power quality big data, while conventional data storage and processing methods are difficult to effectively use big data and explore the value of big data. This paper proposes an online machine learning recognition and classification method for power quality disturbances based on inherent modal function singular value decomposition and least square support vector machines. Aiming at the characteristics of power quality data in distribution networks, this thesis proposes a power quality big data storage scheme based on Mongo DB + Redis, designs a power quality big data processing process, and builds an online machine learning system based on the Apache Spark power quality big data calculation framework.
The Method of Recognizing Bank Card Number Based on MATLAB
Authors: Wang Di
Published: June 2021

In this paper, a quick recognition method of bank card number based on MATLAB is designed, which can identify bank card number automatically. Through the gray processing, edge cutting processing, card number positioning processing, template matching card number recognition and other processing of the bank card image, an accurate and clear bank card number is obtained, which has a certain use value in e-commerce and the Internet. it also provides some reference for image processing and character recognition.