Strong Boundary Research Articles

Evolution of Convective Energy and Inhibition before Instances of Large CAPE

Abstract We analyze the evolution of convective available potential energy (CAPE) and convective inhibition (CIN) in the days leading up to episodes of high CAPE in North America. The widely accepted theory for CAPE buildup, known as the advection hypothesis, states that high moist static energy (MSE) parcels of air moving north from the Gulf of Mexico become trapped under warm but dry parcels moving east from over elevated dry terrain. If and when the resulting CIN erodes, severe convection can occur due to the large energy difference between the boundary layer parcels and cool air aloft. However, our results, obtained via backward Lagrangian tracking of parcels at locations of peak CAPE, show that large values of CAPE are generated mainly via boundary layer moistening in the days leading up to the time of peak CAPE, and that a large portion of this moisture buildup happens on the day of peak CAPE. On the other hand, the free-tropospheric temperature above these tracked parcels rarely changes significantly over the days leading up to such occurrences. In addition, the CIN that allows for this buildup of CAPE arises mostly from unusually strong boundary layer cooling the night before peak CAPE, and has a contribution from differential advection of unusually warm air above the boundary layer to form a capping inversion. These results have important implications for the climatology of severe convective events, as it emphasizes the role of surface properties and their gradients in the frequency and intensity of high CAPE occurrences. Significance Statement Severe convective events, such as thunderstorms, tornadoes, and hail storms, are among the most deadly and destructive weather systems. Although forecasters are quite good at predicting the probability of these events a few days in advance, there is currently no reliable seasonal prediction method of severe convection. We show that the buildup of energy for severe convection relies on both strong surface evaporation during the day of peak energy and anomalous cooling the night before. This progress represents a step toward understanding what controls the frequency of severe convective events on seasonal and longer time scales, including the effect of greenhouse gas–induced climate change.

A Parameter‐Uniform Numerical Scheme for Solving Singularly Perturbed Parabolic Reaction‐Diffusion Problems with Delay in the Spatial Variable

The objective of this research work is to develop and analyse a numerical scheme for solving singularly perturbed parabolic reaction‐diffusion problems with large spatial delay. The presence of the small positive parameter on the term with the highest order of derivative exhibits two strong boundary layers in the solution of the problem, and the large delay term gives rise to a strong interior layer. The layers’ behavior makes it difficult to solve the problem analytically. To treat such a problem, we developed a numerical scheme using the Crank–Nicolson method in the time direction and the central difference method in the spatial direction via nonstandard finite difference methods on uniform meshes. Stability and convergence analyses for the obtained scheme have been established, which show that the developed numerical scheme is uniformly convergent. To confirm the theoretical analysis, model numerical examples are considered and demonstrated.

Unsupervised Legendre–Galerkin Neural Network for Solving Partial Differential Equations

In recent years, machine learning methods have been used to solve partial differential equations (PDEs) and dynamical systems, leading to the development of a new research field called scientific machine learning, which combines techniques such as deep neural networks and statistical learning with classical problems in applied mathematics. In this paper, we present a novel numerical algorithm that uses machine learning and artificial intelligence to solve PDEs. Based on the Legendre-Galerkin framework, we propose an <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">unsupervised machine learning</i> algorithm that learns <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">multiple instances</i> of the solutions for different types of PDEs. Our approach addresses the limitations of both data-driven and physics-based methods. We apply the proposed neural network to general 1D and 2D PDEs with various boundary conditions, as well as convection-dominated <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">singularly perturbed PDEs</i> that exhibit strong boundary layer behavior.

Strong Maximum Principle and Boundary Estimates for Nonhomogeneous Elliptic Equations

We give a simple proof of the strong maximum principle for viscosity subsolutions of fully nonlinear nonhomogeneous degenerate elliptic equations on the formF(x,u,Du,D2u)=0\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$ F(x,u,Du,D^{2}u) = 0 $$\\end{document} under suitable assumptions allowing for non-Lipschitz growth in the gradient term. In case of smooth boundaries, we also prove a Hopf lemma, a boundary Harnack inequality, and that positive viscosity solutions vanishing on a portion of the boundary are comparable with the distance function near the boundary. Our results apply, e.g., to weak solutions of an eigenvalue problem for the variable exponent p-Laplacian.

Lightning Initiation as a Consequence of Natural Thundercloud Evolution. Part 1. The Role of Detachment in Reducing the Critical Air Breakdown Field

Direct measurements show that the maximum values of electric fields measured in thunderclouds are approximately an order of magnitude lower than the air breakdown (ionization threshold) field. At first glance, this means the impossibility of electron avalanches to form and, as a consequence, the impossibility of a lightning discharge to occur. This circumstance puts the question about the lightning origin physical mechanism on a par with the most amazing mysteries of the nature. For more than half a century of research, several mechanisms have been proposed to solve this problem, among which two main lines can be distinguished. The first group of approaches focuses on the possibility of a streamer or a system of streamers to initiate from the surface of one or several hydrometeors, while the second one interprets lightning initiation as a consequence of the runaway electrons breakdown emerging from the interaction between high-energy cosmic rays and the atmosphere. There are also hybrid scenarios that combine both the ideas. However, in view of certain limitations, none of the proposed approaches has been recognized as the final solution to the problem. The article describes a fundamentally new lightning initiation mechanism that develops sequentially on several spatiotemporal scales. The scenario proposed shows how a series of corona discharges occurring during collisions of hydrometeors seeds the cloud with decimeter-scale elevated ionic conductivity regions, the electric field at the poles of which increases to the level necessary for positive streamers to appear. At the next stage, multiple streamer discharges oriented by the direction of a large-scale electric field are combined into a single plasma network, within which a hot leader channel is formed. The mechanism discussed effectively utilizes small-scale and mesoscale electric field fluctuations arising in a thundercloud and can be implemented if the spatiotemporal frequency of corona discharges, accompanying collisions and near collisions of hydrometeors, and the potential difference between the strong intracloud field zone boundaries exceed 0.1 m-3s-1 and 3 MV, respectively. In contrast to alternative approaches, the proposed lightning initiation scenario can be implemented under the conditions of a typical thundercloud without the need to involve any external auxiliary factors. The study results are presented in three parts. This article gives an introductory part, which sets the general context of the narrative and determines the study aims, and describes the role the detachment of electrons from negative ions plays in the air breakdown field reduction. The authors' lightning initiation scenario based on the results described in the present paper is given in two subsequent publications.

Uniform regularity estimates and inviscid limit for the compressible non-resistive magnetohydrodynamics system

We are concerned with the uniform regularity estimates of solutions to the two dimensional compressible non-resistive magnetohydrodynamics (MHD) equations with the no-slip boundary condition on velocity in the half plane. Under the assumption that the initial magnetic field is transverse to the boundary, the uniform conormal energy estimates are established for the solutions to compressible MHD equations with respect to the small viscosity coefficient. As a direct consequence, we proved the inviscid limit of solutions from viscous MHD systems to the ideal MHD systems in sense by some compact arguments. Our results show that the transverse magnetic field near the boundary can prevent the strong boundary layers from occurring.

Impacts of deep boundary layer on near-surface ozone concentration over the Tibetan Plateau

The deep atmospheric boundary layer in winter and spring over the Tibetan Plateau (TP) facilitates the exchange of mass and chemical species between the troposphere and stratosphere. Using ERA5 reanalysis data (1979–2018), this paper analyzes the atmospheric process over the TP when the dynamical tropopause (1.5 PVU surface) approaches the top of the deep boundary layer, which would affect the concentration of near-surface ozone. The result shows that the near-surface (at the height about 500–550 hPa) ozone concentration increases when the tropopause descends and adjoins the top of the deep boundary layer. The influence mechanism of the deep boundary layer on the increase of surface ozone on February 27, 2008 is studied by the WRF-Chem model. It is found that the calculated (using Reynolds average method) near-surface ozone increases by about 8 ppb per hour due to the vertical transport when the ozone-rich air from the stratosphere penetrates into the troposphere. Furthermore, a large eddy simulation (LEM model) is used to investigate the turbulence structure and development during the formation of the deep atmospheric boundary layer in the same case. It is found that a separate weak-turbulence layer forms at the height of about 6000 m AGL at 1300 LT below the tropopause fold. The upper-level turbulence couples with the boundary-layer turbulence after 1900 LT. As a result, the strong boundary layer turbulence causes the ozone-rich air from the stratosphere to mix with air near the surface layer.

Revealing underlying factors of absenteeism: A machine learning approach.

The basis of support is understanding. In machine learning, understanding happens through assimilated knowledge and is centered on six pillars: big data, data volume, value, variety, velocity, and veracity. This study analyzes school attendance problems (SAP), which encompasses its legal statutes, school codes, students' attendance behaviors, and interventions in a school environment. The support pillars include attention to the physical classroom, school climate, and personal underlying factors impeding engagement, from which socio-emotional factors are often the primary drivers. This study asked the following research question: What can we learn about specific underlying factors of absenteeism using machine learning approaches? Data were retrieved from one school system available through the proprietary Building Dreams (BD) platform, owned by the Fight for Life Foundation (FFLF), whose mission is to support youth in underserved communities. The BD platform, licensed to K-12 schools, collects student-level data reported by educators on core values associated with in-class participation (a reported-negative or positive-behavior relative to the core values) based on Social-Emotional Learning (SEL) principles. We used a multi-phased approach leveraging several machine learning techniques (clustering, qualitative analysis, classification, and refinement of supervised and unsupervised learning). Unsupervised technique was employed to explore strong boundaries separating students using unlabeled data. From over 20,000 recorded behaviors, we were able to train a classifier with 90.2% accuracy and uncovered a major underlying factor directly affecting absenteeism: the importance of peer relationships. This is an important finding and provides data-driven support for the fundamental idea that peer relationships are a critical factor affecting absenteeism. The reported results provide a clear evidence that implementing socio-emotional learning components within a curriculum can improve absenteeism by targeting a root cause. Such knowledge can drive impactful policy and programming changes necessary for supporting the youth in communities overwhelmed with adversities.

Screening of global microbiomes implies ecological boundaries impacting the distribution and dissemination of clinically relevant antimicrobial resistance genes

Understanding the myriad pathways by which antimicrobial-resistance genes (ARGs) spread across biomes is necessary to counteract the global menace of antimicrobial resistance. We screened 17939 assembled metagenomic samples covering 21 biomes, differing in sequencing quality and depth, unevenly across 46 countries, 6 continents, and 14 years (2005-2019) for clinically crucial ARGs, mobile colistin resistance (mcr), carbapenem resistance (CR), and (extended-spectrum) beta-lactamase (ESBL and BL) genes. These ARGs were most frequent in human gut, oral and skin biomes, followed by anthropogenic (wastewater, bioreactor, compost, food), and natural biomes (freshwater, marine, sediment). Mcr-9 was the most prevalent mcr gene, spatially and temporally; blaOXA-233 and blaTEM-1 were the most prevalent CR and BL/ESBL genes, but blaGES-2 and blaTEM-116 showed the widest distribution. Redundancy analysis and Bayesian analysis showed ARG distribution was non-random and best-explained by potential host genera and biomes, followed by collection year, anthropogenic factors and collection countries. Preferential ARG occurrence, and potential transmission, between characteristically similar biomes indicate strong ecological boundaries. Our results provide a high-resolution global map of ARG distribution and importantly, identify checkpoint biomes wherein interventions aimed at disrupting ARGs dissemination are likely to be most effective in reducing dissemination and in the long term, the ARG global burden.

A uniformly convergent numerical scheme for solving singularly perturbed differential equations with large spatial delay

In this study, a parameter-uniform numerical scheme is built and analyzed to treat a singularly perturbed parabolic differential equation involving large spatial delay. The solution of the considered problem has two strong boundary layers due to the effect of the perturbation parameter, and the large delay causes a strong interior layer. The behavior of the layers makes it difficult to solve such problem analytically. To treat the problem, we developed a numerical scheme using the weighted average (theta-method) difference approximation on a uniform time mesh and the central difference method on a piece-wise uniform spatial mesh. We established the Stability and convergence analysis for the proposed scheme and obtained that the method is uniformly convergent of order two in the temporal direction and almost second order in the spatial direction. To validate the applicability of the proposed numerical scheme, two model examples are treated and confirmed with the theoretical findings.

Mesoscale eddies in the southwestern tropical Atlantic

The southwestern tropical Atlantic is a region of complex ocean dynamic where originates the strong western boundary current system composed of North Brazil current and North Brazil undercurrent. The region includes a variety of features including the Atoll das Rocas (AR) and Fernando de Noronha (FN) ridge that may favour mesoscale eddy dynamics. However, origin, occurrence and characteristics of mesoscale eddies were still not described in the region. Using satellite altimetry data from 1993 to 2018 off Northeast Brazil (37-25°W; 13-1°S), we reconstruct eddy trajectories and analyse the main eddy surface characteristics (e.g., size, amplitude, polarity) and their spatiotemporal variations. The study reveals two distinct dynamic regions before quantifying mesoscale eddies characteristics. Approximately 2000 mesoscale eddies crossed the region during the study period, among which 76% were generated inside the region, with amplitudes and radii ranging between 1 and 2 cm and 25 and 205 km, respectively. Eddies are preferentially formed between August and September and propagate westward. In the region around the FN Archipelago (36-26°W; 6-1°S), the formation of cyclonic eddies is likely favoured by barotropic instabilities of surface currents and the wind stress curl. On the other hand, in the south of the region (36-26°W; 12-8°S), eddies formation is likely associated with the barotropic instabilities, wind stress curl and the meandering of surface currents. Based on vertical temperature and salinity profiles from Argo floats’ data, we determined that in average, the core of cyclonic eddies is centred at ~ 130 m (140 m) in the northern (southern) region while the core of anticyclonic eddies is centred at ~90 m (125 m) in the northern (southern) region. Moreover, mesoscale eddies formed in the tropical Atlantic do not connect the eastern tropical Atlantic and northeast Brazil.

Numerical treatment of singularly perturbed parabolic partial differential equations with nonlocal boundary condition

This paper presents numerical treatments for a class of singularly perturbed parabolic partial differential equations with nonlocal boundary conditions. The problem has strong boundary layers atx= 0 andx= 1. The nonstandard finite difference method was developed to solve the considered problem in the spatial direction, and the implicit Euler method was proposed to solve the resulting system of IVPs in the temporal direction. The nonlocal boundary condition is approximated by Simpsons13rule. The stability and uniform convergence analysis of the scheme are studied. The developed scheme is second-order uniformly convergent in the spatial direction and first-order in the temporal direction. Two test examples are carried out to validate the applicability of the developed numerical scheme. The obtained numerical results reflect the theoretical estimate.

Optical microscope with a large tilt angle and a long focal length for a nano-size angle-resolved photoemission spectroscopy.

Angle-resolved photoemission spectroscopy with nanoscale spatial resolution (Nano-ARPES) is a powerful tool for the investigation of electronic structures of materials and their spatial configurations. In order to capture the area of interest in Nano-ARPES measurements effectively, an optical microscope can be used to provide real space optical images as a reference. In this work, a new type of optical microscope for Nano-APRES spectrometer with a large tilt angle of ∼30 degrees and a long focal length of ∼12 mm has been designed. Large magnifications by 7 × to 20 × and a spatial resolution of 3 um have been achieved, which can effectively assist optical alignment for Nano-ARPES. In addition, the strong boundary sensitivity observed in such a tilt design demonstrates its special capability in detecting the fine features of surface coarseness.

Synergistic Lubrication for Textured Surfaces Using Polar and Nonpolar Lubricants

Abstract The synergistic effect of surface texturing and lubricants with various viscosity and polarity properties is an attractive and unexplored topic. In this study, surface texturing characterized by circular dimples has been manufactured on steel surfaces in advance, which can improve the lubrication of frictional units compared with the bare disc under different lubricants. Then, three lubricants, low-viscosity and nonpolar white oil, high viscosity and nonpolar silicone oil, and highly viscous and polar castor oil, were used to evaluate the interaction between surface texture and the lubricating oil. The contact angles of each lubricant on the textured and bare surface were measured to investigate the lubricant intermolecular force and wettability. The oil film thickness simulation and tribological experiments were conducted. The tribological results indicate that lubricants with varied characteristics work differently due to their different properties on textured surfaces. Castor oil exhibits the best tribological properties of the three oils used to supply the textured surfaces, which may attribute to its ability to generate strong boundary adsorption films as well as a thickened interfacial layer, and it could reduce the intensity of asperity interaction.

Performance of CMIP6 models in simulating the dynamic sea level: Mean and interannual variance

Observational data from satellite altimetry were used to quantify the performance of CMIP6 models in simulating the climatological mean and interannual variance of the dynamic sea level (DSL) over 40°S–40°N. In terms of the mean state, the models generally agree well with observations, and high consistency is apparent across different models. The largest bias and model discrepancy is located in the subtropical North Atlantic. As for simulation of the interannual variance, good agreement can be seen across different models, yet the models present a relatively low agreement with observations. The simulations show much weaker variance than observed, and bias is apparent over the subtropics in association with strong western boundary currents. This nearshore bias is reduced considerably in HighResMIP models. The underestimation of DSL interannual variance is at least partially due to the misrepresentation of ocean processes in the CMIP6 historical simulation with its relatively low resolution. The results identify directions for future model development towards a better understanding of the mean and interannual variability of DSL.摘要本研究采用卫星测高数据与第六次国际耦合模式比较计划 (CMIP6) 海平面动力进行对比, 重点针对40°S–40°N地区的动力海平面 (DSL) , 评估了模式对其平均态与年际变率的综合模拟能力. 结果表明, 对于DSL平均态的模拟, 模式与观测结果非常吻合, 模式之间的差异较小. 其中, 副热带北大西洋是模拟偏差和模式间差异较为显著的区域. 对于DSL年际变率的模拟, 模式之间保持较高的一致性, 但是, 模式与观测结果存在明显差异, 模式普遍低估了DSL的年际方差; 其中, 误差大值区域出现在副热带西边界流附近. 模式分辨率会影响CMIP6对中小尺度海洋过程的重现能力, 这可能是导致CMIP6历史模拟出现误差的原因之一.

Encapsulated layer induces boundary effect and twist angle adjust absorption in h-BN/graphene/h-BN heterostructure

This work studied the optical absorption properties and electronic properties of graphene nanosheets encapsulated in h-BN at different twisted angles based on first principles. UV–Vis spectrum shows that compared with the monolayer graphene nanosheets, the absorption’s peak of the encapsulated graphene nanosheets show a red shift and its molar absorption coefficient decreased significantly. The molar absorption coefficients of h-BN/graphene/h-BN heterostructures show an increasing trend when the graphene nanosheets are twisted relative to the packaging layer (twisted angles are 0°, 15°, 21.8°, 27.8° and 30°, respectively). More curiously, charge density difference (CDD) indicates that the region of electron aggregation in excited state mainly occurs at the centre of graphene nanosheets due to the introduction of h-BN packaging layer. The smoothed isosurface diagram of electron hole pairs shows that the distribution breadth of electron hole pair density decreases compared with that before encapsulation, and the distribution breadth of electron increase is larger than that of hole. With the increase of twisted angles, the distribution breadth of electron hole pair density increases gradually. Both CDD and smoothed isosurface diagram show that the system has strong boundary effect. This provides a method to adjust the photoelectric properties of graphene nanosheets by using different twisted angles, and provides a theoretical basis for its application in the field of micro-nano optoelectronics.

Solving singularly perturbed delay differential equations via fitted mesh and exact difference method

In this paper, different numerical schemes are developed and investigated for solving singularly perturbed delay differential equations (DDEs). The solution of the considered equations exhibits a strong boundary layer when the perturbation parameter approaches zero. Standard numerical methods developed for solving regular problems fail to treat accurately the considered equations. We developed three numerical schemes for treating the considered equations. The first scheme (Scheme I) uses a non-standard mid-point upwind finite difference method on uniform mesh; the second scheme (Scheme II) uses a standard mid-point upwind finite difference method on Shiskin mesh and the third scheme (Scheme III) uses a non-standard mid-point upwind finite difference method on Shiskin mesh. The existence of a unique discrete solution is investigated using the discrete maximum principle. The stability and uniform convergence of the schemes are investigated and proved. Scheme III gives better accuracy and order of convergence than Scheme I. It has a boundary layer resolving behaviour which is the main drawback of Scheme II. Numerical examples are considered and treated to validate the theoretical finding of the schemes for different values of the perturbation parameter and delay parameter.

CENN: Conservative energy method based on neural networks with subdomains for solving variational problems involving heterogeneous and complex geometries

We propose a conservative energy method based on neural networks with subdomains for solving variational problems (CENN), where the admissible function satisfying the essential boundary condition without boundary penalty is constructed by the radial basis function (RBF), particular solution neural network, and general neural network. Loss term is the potential energy, optimized based on the principle of minimum potential energy. The loss term at the interfaces has the lower order derivative compared to the strong form PINN with subdomains. The advantage of the proposed method is higher efficiency, more accurate, and less hyperparameters than the strong form PINN with subdomains. Another advantage of the proposed method is that it can apply to complex geometries based on the special construction of the admissible function. To analyze its performance, the proposed method CENN is used to model representative PDEs, the examples include strong discontinuity, singularity, complex boundary, non-linear, and heterogeneous problems. Furthermore, it outperforms other methods when dealing with heterogeneous problems.

The Kuroshio Regulates the Air-Sea Exchange of PCBs in the Northwestern Pacific Ocean.

Calculating accurate air-sea fluxes for polychlorinated biphenyls (PCBs) is an essential condition for evaluating their transport in the atmosphere. A three-dimensional hydrodynamic-ecosystem-PCB coupled model was developed for the northwestern Pacific Ocean to assess the air-sea fluxes of four PCBs and examine the influences of ocean currents on the fluxes. The model revealed a fine structure in the air-sea flux that is sensitive to the Kuroshio, a western boundary current with a high surface speed. Intense downward and upward fluxes (-23.6 to 44.75 ng m-2 d-1 for ∑4PCBs) can be found in the Kuroshio region south of Japan and the Kuroshio Extension east of Japan, respectively. In strong (weak) current regions, it takes ∼4 and ∼1 days (1-3 and 3-12 days) for dissolved PCBs to reach an equilibrium in scenarios where only air-sea exchange or only ocean advection is considered, respectively. In strong current regions, the ocean advection has a shorter response time than the air-sea exchange, indicating that dissolved PCBs from upstream carried by strong current can easily change the downstream concentration by disrupting the equilibrium with original air-sea exchange and induce new air-sea fluxes there. Therefore, strong western boundary currents should be correctly considered in future atmospheric transport models for PCBs.

Temperature dependence of tensile behavior, deformation mechanisms and fracture in nitrogen-alloyed FeMnCrNiCo(N) Cantor alloys

Among a family of the multi-principle-element alloys, a high-entropy Cantor alloy attracts much attention due to the striking temperature dependence of strength properties, strong grain boundary hardening and the excellent low-temperature ductility. Cantor alloy is a substitutional concentrated solid solution, thus, its strength properties and strain hardening could be additionally enhanced by interstitial hardening. Here we explore the effect of nitrogen alloying with atomic concentrations of 0.8%, 1.4% and 1.6% on a temperature dependence (temperature range from 77 to 473 K) of the microstructure, mechanical properties, and fracture micromechanisms of FeMnCrNiCo alloy with the focus on low-temperature deformation regime. Nitrogen-alloying promotes the expansion of a crystal lattice with a linear increase of a lattice parameter of the alloy with nitrogen content, ∆a/∆CN = 0.625 pm/at%. Nitrogen-bearing FeMnCrNiCo(N) alloys possess stronger temperature dependence of a yield strength relative to the Cantor alloy, and nitrogen forces both athermal and thermal components of the stress. The solid-solution strengthening of Cantor alloy is proportional to the nitrogen concentration Δτ ~ CN, and the value (ΔYS/ΔCN) for the coarse-grained FeMnCrNiCo(N) alloys is a temperature-dependent parameter (ΔYS/ΔCN = 97 MPa/at% at RT and ΔYS/ΔCN = 146 MPa/at% at 77 K). Dislocation slip is a dominating deformation mechanism of the nitrogen-alloyed alloys along the whole range of the deformation temperatures. A decrease in test temperature and nitrogen-alloying both force the tendency to the planar slip and facilitate strain hardening. Despite a weak effect of nitrogen on a stacking fault energy of the Cantor alloy and high deforming stresses in FeMnCrNiCo(N) alloys, nitrogen-containing alloys show low activity of the mechanical twinning. Opposite effects of the nitrogen-alloying on the elongation of the Cantor alloy were found for different deformation regimes: positive at T > 250 K (elongation increases with nitrogen-alloying) and negative at T < 250 K (it decreases in nitrogen-bearing alloys). For FeMnCrNiCo(N) alloys, the appearance of the ductile-to-brittle transition in low-temperature deformation regime is associated with the brittle intergranular fracture of the specimens alloyed with nitrogen CN ≥ 1.4 at%.