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Sensitivity of wheat and rice to low levels of atmospheric ethylene

Ethylene (C2H4) gas is produced throughout the life cycle of plants and can accumulate in closed growth chambers to levels 100 times higher than in outside environments. Elevated atmospheric C2H4 can cause a variety of abnormal responses, but the sensitivity to elevated C2H4 is not well characterized. We evaluated the C2H4 sensitivity of wheat (Triticum aestivum L.) and rice (Oryza sativa L.) in five studies. The first three studies compared the effects of continuous C2H4 levels ranging from 0 to 1000 nmol mol-1 (ppb) in a growth chamber throughout the life cycle of the plants. A short-term 1000 nmol mol-1 treatment was included in which exposure was stopped at anthesis. Yield was reduced by 36% in wheat and 63% in rice at 50 nmol mol-1 and both species were virtually sterile when continuously exposed to 1000 nmol mol-1. However, the yield reductions were much less with exposure that stopped at anthesis, suggesting the detrimental effect of C2H4 on yield was greatest around the time of seed set. Two additional studies evaluated the differential sensitivity of two wheat cultivars (Super Dwarf and USU-Apogee) to 50 nmol mol-1 C2H4 at three CO2 levels [350, 1200, 5000 micromoles mol-1 (ppm)] in a greenhouse. Yield of USU-Apogee was not significantly reduced by C2H4 but the yield of Super Dwarf was reduced by 60%. Elevated CO2 did not influence the sensitivity to C2H4. A difference in the C2H4 sensitivity of USU-Apogee between greenhouse and growth chamber trials suggests that C2H4 sensitivity is dependent on the environment. Collectively, the data suggest that relatively low levels of C2H4 could induce anomalous plant responses by accumulation in greenhouses and growth chambers with inadequate ventilation. The data also suggest that C2H4 sensitivity can be reduced by both genetic and environmental manipulations. 2002 Crop Science Society of America.

NASA Discipline Life Sciences Technologies↗

Thermal Performance of Cryogenic Multilayer Insulation at Various Layer Spacings

Multilayer insulation (MLI) has been shown to be the best performing cryogenic insulation system at high vacuum (less that 10 (exp 3) torr), and is widely used on spaceflight vehicles. Over the past 50 years, many investigations into MLI have yielded a general understanding of the many variables that are associated with MLI. MLI has been shown to be a function of variables such as warm boundary temperature, the number of reflector layers, and the spacer material in between reflectors, the interstitial gas pressure and the interstitial gas. Since the conduction between reflectors increases with the thickness of the spacer material, yet the radiation heat transfer is inversely proportional to the number of layers, it stands to reason that the thermal performance of MLI is a function of the number of layers per thickness, or layer density. Empirical equations that were derived based on some of the early tests showed that the conduction term was proportional to the layer density to a power. This power depended on the material combination and was determined by empirical test data. Many authors have graphically shown such optimal layer density, but none have provided any data at such low densities, or any method of determining this density. Keller, Cunnington, and Glassford showed MLI thermal performance as a function of layer density of high layer densities, but they didn't show a minimal layer density or any data below the supposed optimal layer density. However, it was recently discovered that by manipulating the derived empirical equations and taking a derivative with respect to layer density yields a solution for on optimal layer density. Various manufacturers have begun manufacturing MLI at densities below the optimal density. They began this based on the theory that increasing the distance between layers lowered the conductive heat transfer and they had no limitations on volume. By modifying the circumference of these blankets, the layer density can easily be varied. The simplest method of determining the thermal performance of MLI at cryogenic temperature is by boil-off calorimetry. Several blankets were procured and tested at various layer densities at the Cryogenics Test Laboratory at Kennedy Space Center. The densities that the blankets were tested over covered a wide range of layer densities including the analytical minimum. Several of the blankets were tested at the same insulation thickness while changing the layer density (thus a different number of reflector layers). Optimizing the layer density of multilayer insulation systems for heat transfer would remove a layer density from the complex method of designing such insulation systems. Additional testing was performed at various warm boundary temperatures and pressures. The testing and analysis was performed to simplify the analysis of cryogenic thermal insulation systems. This research was funded by the National Aeronautics and Space Administration's Exploration Technology Development Program's Cryogenic Fluid Management Project

Johnson, Wesley Louis↗

NASA Tech Briefs, Februrary 2013

Topics covered include: Measurements of Ultra-Stable Oscillator (USO) Allan Deviations in Space; Gaseous Nitrogen Orifice Mass Flow Calculator; Validation of Proposed Metrics for Two-Body Abrasion Scratch Test Analysis Standards; Rover Low Gain Antenna Qualification for Deep Space Thermal Environments; Automated, Ultra-Sterile Solid Sample Handling and Analysis on a Chip; Measuring and Estimating Normalized Contrast in Infrared Flash Thermography; Spectrally and Radiometrically Stable, Wideband, Onboard Calibration Source; High-Reliability Waveguide Vacuum/Pressure Window; Methods of Fabricating Scintillators With Radioisotopes for Beta Battery Applications; Magnetic Shield for Adiabatic Demagnetization Refrigerators (ADR); CMOS-Compatible SOI MESFETS for Radiation-Hardened DC-to-DC Converters; Silicon Heat Pipe Array; Adaptive Phase Delay Generator; High-Temperature, Lightweight, Self-Healing Ceramic Composites for Aircraft Engine Applications; Treatment to Control Adhesion of Silicone-Based Elastomers; High-Temperature Adhesives for Thermally Stable Aero-Assist Technologies; Rockballer Sample Acquisition Tool; Rock Gripper for Sampling, Mobility, Anchoring, and Manipulation; Advanced Magnetic Materials Methods and Numerical Models for Fluidization in Microgravity and Hypogravity; Data Transfer for Multiple Sensor Networks Over a Broad Temperature Range; Using Combustion Synthesis to Reinforce Berms and Other Regolith Structures; Visible-Infrared Hyperspectral Image Projector; Three-Axis Attitude Estimation With a High-Bandwidth Angular Rate Sensor Change_Detection.m; AGATE: Adversarial Game Analysis for Tactical Evaluation; Ionospheric Simulation System for Satellite Observations and Global Assimilative; Modeling Experiments (ISOGAME); An Extensible, User- Modifiable Framework for Planning Activities; Mission Operations Center (MOC) - Precipitation Processing System (PPS) Interface Software System (MPISS); Automated 3D Damaged Cavity Model Builder for Lower Surface Acreage Tile on Orbiter; Mixed Linear/Square-Root Encoded Single-Slope Ramp Provides Low-Noise ADC with High Linearity for Focal Plane Arrays; RUSHMAPS: Real-Time Uploadable Spherical Harmonic Moment Analysis for Particle Spectrometers; Powered Descent Guidance with General Thrust-Pointing Constraints; X-Ray Detection and Processing Models for Spacecraft Navigation and Timing; and Extreme Ionizing-Radiation-Resistant Bacterium

Source record↗

UAV Research at NASA Langley: Towards Safe, Reliable, and Autonomous Operations

Unmanned Aerial Vehicles (UAV) are fundamental components in several aspects of research at NASA Langley, such as flight dynamics, mission-driven airframe design, airspace integration demonstrations, atmospheric science projects, and more. In particular, NASA Langley Research Center (Langley) is using UAVs to develop and demonstrate innovative capabilities that meet the autonomy and robotics challenges that are anticipated in science, space exploration, and aeronautics. These capabilities will enable new NASA missions such as asteroid rendezvous and retrieval (ARRM), Mars exploration, in-situ resource utilization (ISRU), pollution measurements in historically inaccessible areas, and the integration of UAVs into our everyday lives all missions of increasing complexity, distance, pace, and/or accessibility. Building on decades of NASA experience and success in the design, fabrication, and integration of robust and reliable automated systems for space and aeronautics, Langley Autonomy Incubator seeks to bridge the gap between automation and autonomy by enabling safe autonomous operations via onboard sensing and perception systems in both data-rich and data-deprived environments. The Autonomy Incubator is focused on the challenge of mobility and manipulation in dynamic and unstructured environments by integrating technologies such as computer vision, visual odometry, real-time mapping, path planning, object detection and avoidance, object classification, adaptive control, sensor fusion, machine learning, and natural human-machine teaming. These technologies are implemented in an architectural framework developed in-house for easy integration and interoperability of cutting-edge hardware and software.

Davila, Carlos G.↗

Human Factors and Behavioral Performance Exploration Measures Harmonized Across HERA, NEK, And ISS: Behavioral Medicine Risk

The Human Factors and Behavioral Performance Exploration Measures (HFBP-EM) suite is a set of standardized measures used to assess behavioral health and performance risks related to future exploration class space missions. The HFBP-EM addresses the Human Research Program’s (HRP) Behavioral Medicine (BMed), Team, Sleep, and Human Systems Integration Architecture risks. HFBP-EM were collected during Human Exploration Research Analog (HERA) campaigns 4 and 5, and during SIRIUS 17 and 19 missions in the Russian Ground Based Experiment Complex, NEK, to document the feasibility, flexibility, and acceptability of these measures in analogs of spaceflight environments. A subset of the HFBP-EM suite was collected in spaceflight as part of the HRP Standard Measures in Spaceflight Project. Whenever possible, the HFBP-EM protocol and measures are the same across studies, differences across research settings (e.g., experimental manipulations, mission scenarios, and mission length) and implementation of the measures require that the data are harmonized to ensure comparable views across missions. The purpose of our project was to develop a harmonized database of analyzable HFBP-EM data from spaceflight and analog settings, and to summarize the trajectory of behavioral health and performance outcomes within and between mission settings. In this presentation, we will summarize the harmonized dataset and the trajectory of BMed related measures including depression, neurobehavioral function, mood, cognition, and operationally relevant individual performance over time and by campaign and mission.

S T Bell↗

Command and Control System Automated Testing

The Kennedy Space Center (KSC) has developed its own Command and Control System for the launch of the Space Launch System (SLS) and Orion capsule. The Command and Control System (CCS) is used by console engineers for the launch and system checkout of aerospace vehicles. The CCS allows console engineers to read data from the flight hardware on the launch pad and from the ground control systems and allows console engineers to issue commands, like opening a valve, to the flight hardware and ground control systems. The CCS needs to interact with thousands of devices and hardware controllers for the spacecraft and ground systems, receive data from these devices, distribute the data to console engineers in real-time, and allow console engineers to issue commands to manipulate hardware on the launch pad. The system needs to be robust, fault tolerant, responsive, and fast. In order to keep up with the pace of development of the CCS, a Test Automation System (TAS) is needed to validate the integrity of the system as a whole along with its individual components. Automated tests allow for faster development time, since tests can be ran through a Continuous Integration system and allow developers to check their code faster. Currently, the different modules, classes, and functions that make up the CCS are tested at the unit level, and the system level, with all the modules working together. My project was to implement a system for the data protocol layer of the Command Control System to be tested as a complete functional unit, with all of its classes and functions working together, but independent of the other modules of the CCS.

Automated TestingTest Automation↗

A theoretical and experimental investigation of impact control for manipulators

This article describes a simple control strategy for stable hardon-hard contact of a manipulator with the environment. The strategy is motivated by recognition of the equivalence of proportional gain explicit force control and impedance control. It is shown that negative proportional force gains, or impedance mass ratios less than unity, can equivalently provide excellent impact response without bouncing. This result is indicated by an analysis performed with an experimentally determined arm/sensor/environment model. The results are corroborated by experimental data from implementation of the control algorithms on the CMU DD Arm II system. The results confirm that manipulator impact against a stiff environment without bouncing can be readily handled by this novel control strategy.

Volpe, Richard↗

MASCOT - MATLAB Stability and Control Toolbox

MASCOT software was created to provide the conceptual aircraft designer accurate predictions of air vehicle stability and control characteristics. The code takes as input mass property data in the form of an inertia tensor, aerodynamic loading data, and propulsion (i.e. thrust) loading data. Using fundamental non-linear equations of motion, MASCOT then calculates vehicle trim and static stability data for any desired flight condition. Common predefined flight conditions are included. The predefined flight conditions include six horizontal and six landing rotation conditions with varying options for engine out, crosswind and sideslip, plus three takeoff rotation conditions. Results are displayed through a unique graphical interface developed to provide stability and control information to the conceptual design engineers using a qualitative scale indicating whether the vehicle has acceptable, marginal, or unacceptable static stability characteristics. This software allows the user to prescribe the vehicle s CG location, mass, and inertia tensor so that any loading configuration between empty weight and maximum take-off weight can be analyzed. The required geometric and aerodynamic data as well as mass and inertia properties may be entered directly, passed through data files, or come from external programs such as Vehicle Sketch Pad (VSP). The current version of MASCOT has been tested with VSP used to compute the required data, which is then passed directly into the program. In VSP, the vehicle geometry is created and manipulated. The aerodynamic coefficients, stability and control derivatives, are calculated using VorLax, which is now available directly within VSP. MASCOT has been written exclusively using the technical computing language MATLAB . This innovation is able to bridge the gap between low-fidelity conceptual design and higher-fidelity stability and control analysis. This new tool enables the conceptual design engineer to include detailed static stability and trim constraints in the conceptual design loop. The unique graphical interface developed for this tool presents the stability data in a format that is understandable by the conceptual designer, yet also provides the detailed quantitative results if desired.

Kenny, Sean↗

Real time data acquisition for expert systems in Unix workstations at Space Shuttle Mission Control

A distributed system of proprietary engineering-class workstations is incorporated into NASA's Space Shuttle Mission-Control Center to increase the automation of mission control. The Real-Time Data System (RTDS) allows the operator to utilize expert knowledge in the display program for system modeling and evaluation. RTDS applications are reviewed including: (1) telemetry-animated communications schematics; (2) workstation displays of systems such as the Space Shuttle remote manipulator; and (3) a workstation emulation of shuttle flight instrumentation. The hard and soft real-time constraints are described including computer data acquisition, and the support techniques for the real-time expert systems include major frame buffers for logging and distribution as well as noise filtering. The incorporation of the workstations allows smaller programming teams to implement real-time telemetry systems that can improve operations and flight testing.

Muratore, John F.↗

Multivariate statistical analysis software technologies for astrophysical research involving large data bases

We developed a package to process and analyze the data from the digital version of the Second Palomar Sky Survey. This system, called SKICAT, incorporates the latest in machine learning and expert systems software technology, in order to classify the detected objects objectively and uniformly, and facilitate handling of the enormous data sets from digital sky surveys and other sources. The system provides a powerful, integrated environment for the manipulation and scientific investigation of catalogs from virtually any source. It serves three principal functions: image catalog construction, catalog management, and catalog analysis. Through use of the GID3* Decision Tree artificial induction software, SKICAT automates the process of classifying objects within CCD and digitized plate images. To exploit these catalogs, the system also provides tools to merge them into a large, complete database which may be easily queried and modified when new data or better methods of calibrating or classifying become available. The most innovative feature of SKICAT is the facility it provides to experiment with and apply the latest in machine learning technology to the tasks of catalog construction and analysis. SKICAT provides a unique environment for implementing these tools for any number of future scientific purposes. Initial scientific verification and performance tests have been made using galaxy counts and measurements of galaxy clustering from small subsets of the survey data, and a search for very high redshift quasars. All of the tests were successful, and produced new and interesting scientific results. Attachments to this report give detailed accounts of the technical aspects for multivariate statistical analysis of small and moderate-size data sets, called STATPROG. The package was tested extensively on a number of real scientific applications, and has produced real, published results.

Djorgovski, S. George↗

Multivariate Statistical Analysis Software Technologies for Astrophysical Research Involving Large Data Bases

We developed a package to process and analyze the data from the digital version of the Second Palomar Sky Survey. This system, called SKICAT, incorporates the latest in machine learning and expert systems software technology, in order to classify the detected objects objectively and uniformly, and facilitate handling of the enormous data sets from digital sky surveys and other sources. The system provides a powerful, integrated environment for the manipulation and scientific investigation of catalogs from virtually any source. It serves three principal functions: image catalog construction, catalog management, and catalog analysis. Through use of the GID3* Decision Tree artificial induction software, SKICAT automates the process of classifying objects within CCD and digitized plate images. To exploit these catalogs, the system also provides tools to merge them into a large, complex database which may be easily queried and modified when new data or better methods of calibrating or classifying become available. The most innovative feature of SKICAT is the facility it provides to experiment with and apply the latest in machine learning technology to the tasks of catalog construction and analysis. SKICAT provides a unique environment for implementing these tools for any number of future scientific purposes. Initial scientific verification and performance tests have been made using galaxy counts and measurements of galaxy clustering from small subsets of the survey data, and a search for very high redshift quasars. All of the tests were successful and produced new and interesting scientific results. Attachments to this report give detailed accounts of the technical aspects of the SKICAT system, and of some of the scientific results achieved to date. We also developed a user-friendly package for multivariate statistical analysis of small and moderate-size data sets, called STATPROG. The package was tested extensively on a number of real scientific applications and has produced real, published results.

Djorgovski, S. G.↗

Electrochemical Manipulation and Radiolytic Evaluation of Organic Phase Neptunium

Presentation for Seed LDRD proposal presentation: This Seed LDRD research proposes to test an innovative approach to precisely control the oxidation state distribution of neptunium (Np) under used nuclear fuel (UNF) reprocessing conditions using novel electrochemical methods. Current UNF reprocessing technologies are not financially viable in the US, requiring significant scientific and technological innovation to improve cost efficiency. Reducing the number of process cycles is one avenue for increasing cost efficiency, of which resolving the challenge associated with isolating Np is critical. Under envisioned process conditions, Np is present in a mixture of extractable (Np(IV) and Np(VI)) and inextractable (Np(V)) oxidation states, the distribution of which is dependent on several factors, including ionizing radiation dose, that change throughout a reprocessing scheme. Consequently, Np unintentionally partitions into various UNF reprocessing phases and product streams, ultimately increasing the number of process cycles to isolate UNF components. Here, we propose to employ novel, high surface area, optically transparent, Ligand Modified tin-doped indium oxide Electrodes (LMES). These LMEs bind Np, and therefore enable concurrent generation and spectroscopic characterization of Np oxidation states in organic solutions. These proof-of-concept experiments will: (i) facilitate optimization of the proposed electrochemical system conditions for Np oxidation state manipulation; (ii) identify the accessible electrochemical window for Np complexes in the organic phase; (iii) report characteristic optical spectra for each accessible complexed Np oxidation state; and (iv) determine the lifetime and partitioning of a given atypical Np oxidation state in the organic phase in the presence and absence of ionizing radiation fields. The data gathered by this Seed LDRD will provide support for the design of an electrochemical process concept for the precise manipulation of Np oxidation states in UNF reprocessing solvent systems, with the intention of providing advanced control over Np mass transfer, and thus greater process efficiency and economy.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Improving evapotranspiration computation with electrical resistivity tomography in a maize field

Abstract Hydrogeophysical methods have been increasingly used to study subsurface soil–water dynamics, yet their application beyond the soil compartment or the quantitative link to soil hydraulic properties remains limited. To examine how these methods can inform model‐based evapotranspiration (ET) calculation under varying soil water conditions, we conducted a pilot‐scale field study at an experimental maize plot with manipulated irrigation treatments. Our goal was to develop a workflow for (1) acquiring and inverting field electrical resistivity tomography (ERT) data, (2) correlating ERT to soil hydraulic properties, (3) spatially characterizing soil water stress that feeds into ET modeling (the FAO‐56 model), and (4) evaluating the performance of ERT‐based ET computation. Our results showed that ERT was able to capture decimeter‐scale soil water content (SWC) dynamics from root water uptake and irrigation manipulation and the contrast of soil water stress between deficiently and fully irrigated maize. We also demonstrated the flexibility of using ERT to spatially integrate soil water stress in the soil volume of interest, which could be adjusted based on different crops and plot layouts. The integration of the ERT datasets into ET modeling provided insights into the spatial heterogeneity of the subsurface that has been challenging for point‐based sensing, which can further our understanding of the hydraulic dynamics in the soil‐plant‐atmosphere continuum.

54 ENVIRONMENTAL SCIENCES↗

Machine Learning for Real-time Fusion Plasma Behavior Prediction and Manipulation (Final Report)

The goal of this project is to implement real-time analysis of 2D Beam Emission Spectroscopy (BES) data to predict and control transient and high-bandwidth events at DIII-D. In essence, we wish to bring high-bandwidth fluctuation diagnostics into the realm of real-time measurements and control. The BES ML models will necessarily be deep neural networks (DNN) with a “data flow” architecture for compatibility with high-throughput, low-latency evaluation on a field-programmable gate array (FPGA) or other emerging processor technologies. The real-time output will be fed to the plasma control system (PCS) for real-time control tasks, specifically for ELM control and avoidance and for QH-mode access and sustainment. We anticipate that the real-time analysis of fluctuation diagnostics will create new enabling technologies to predict and control transient events such as confinement mode transitions, edge-localized modes, Alfven eigenmode events, and disruptions. The proposed research is aligned with ITER research needs and DIII-D programmatic goals. For instance, the prediction and avoidance of ELM events is critical for ITER machine safety. Also, H-mode access with RMP ELM suppression in ITER is an active research area due to high separatrix density, narrow SOL width, and elevated LH transition power threshold.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Parameter identification for a robotic manipulator arm

The development is described of a nonlinear dynamic model for large oscillations of a robotic manipulator arm about a single joint. Optimization routines are formulated and implemented for the identification of electrical and physical parameters from dynamic data taken from an industrial robot arm. Special attention is given to the role of sensitivity in the formulation of robust models of this motion. The importance of actuator effects in the reduction of sensitivity is established and used to develop an electromechanical model of the manipulator system.

Brewer, D. W.↗

Inferring microbial interactions with their environment from genomic and metagenomic data

Microbial communities assemble through a complex set of interactions between microbes and their environment, and the resulting metabolic impact on the host ecosystem can be profound. Microbial activity is known to impact human health, plant growth, water quality, and soil carbon storage which has lead to the development of many approaches and products meant to manipulate the microbiome. In order to understand, predict, and improve microbial community engineering, genome-scale modeling techniques have been developed to translate genomic data into inferred microbial dynamics. However, these techniques rely heavily on simulation to draw conclusions which may vary with unknown parameters or initial conditions, rather than more robust qualitative analysis. To better understand microbial community dynamics using genome-scale modeling, we provide a tool to investigate the network of interactions between microbes and environmental metabolites over time. Using our previously developed algorithm for simulating microbial communities from genome-scale metabolic models (GSMs), we infer the set of microbe-metabolite interactions within a microbial community in a particular environment. Because these interactions depend on the available environmental metabolites, we refer to the networks that we infer as metabolically contextualized , and so name our tool MetConSIN: Met abolically Con textualized S pecies I nteraction N etworks.

59 BASIC BIOLOGICAL SCIENCES↗

Estimating carrying capacity for juvenile salmon using quantile random forest models

Abstract Establishing robust methods and metrics to evaluate habitat quality is critical for the recovery of endangered Pacific salmonids ( Oncorhynchus spp.). A variety of modeling approaches are used for status and trend monitoring of anadromous species throughout the Pacific Northwest, USA, but current methods may fail to capture the complex relationship between fish and habitat and are often limited in predictive power beyond specific watersheds. Further, the focus on species distribution and abundance is not easily manipulated to predict carrying capacity and traditional stock‐recruitment analyses are reliant on long‐term data which are not always available. In this study, we developed a quantile random forest model to provide estimates of habitat carrying capacity for Chinook salmon ( O. tshawytscha ) parr during the summer months, at both the site and watershed scale. Quantile random forest models allow for the consideration of noisy data, correlated variables, and non‐linear relationships: common features in fish–habitat datasets. We leveraged Columbia Habitat Monitoring Program data to select habitat co‐variates and predict capacity at those sites. We also identified a set of globally available attributes to extrapolate capacity estimate predictions throughout wadeable streams within the Columbia River basin. Total capacity estimates for watersheds closely matched estimates from alternative fish productivity models. Carrying capacity estimates based on quantile random forest models, like those presented here, provide managers a framework to guide the identification, prioritization, and development of habitat rehabilitation actions to recover salmon populations.

See, Kevin E.↗

Stabilization and control of topological magnetic solitons via magnetic nanopatterning of exchange bias systems

Stabilizing and manipulating topological magnetic quasiparticles in thin films is of great interest for potential applications in data storage and information processing. Here, we present a strategy for stabilizing magnetic vortices and Bloch lines with controlled position, vorticity, and chirality in a continuous exchange bias system. By tailoring vectorially the unidirectional anisotropy of the system at the nanoscale, via thermally assisted magnetic scanning probe lithography, we show experimentally and via micromagnetic simulations the non-volatile creation of vortex-antivortex pairs. In addition, we demonstrate the deterministic stabilization of cross and circular Bloch lines within patterned Néel magnetic domain walls. This work enables the implementation of complex functionalities based on the control of tailored topological spin-textures in spintronic and magnonic nanodevices.

Magnetic ordering↗