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Background Both predictions and predictors of difficult laryngoscopy are controversial. Machine learning is an excellent alternative method for predicting difficult laryngoscopy. This study aimed to develop and validate practical predictive models for difficult laryngoscopy through machine learning. Methods Variables for the prediction of difficult laryngoscopy included age, Mallampati grade, body mass index, sternomental distance, and neck circumference. Difficult laryngoscopy was defined as grade 3 and 4 by the Cormack-Lehane classification. Pre-anesthesia and anesthesia data of 616 patients who had undergone anesthesia at a single center were included. The dataset was divided into a base training set (n = 492) and a base test set (n = 124), with equal distribution of difficult laryngoscopy. Training data sets were trained with six algorithms (multilayer perceptron, logistic regression, supportive vector machine, random forest, extreme gradient boosting, and light gradient boosting machine), and cross-validated. The model with the highest area under the receiver operating characteristic curve (AUROC) was chosen as the final model, which was validated with the test set. Results The results of cross-validation were best using the light gradient boosting machine algorithm with Mallampati score x age and sternomental distance as predictive model parameters. The predicted AUROC for the difficult laryngoscopy class was 0.71 (95% confidence interval, 0.59–0.83; p = 0.014), and the recall (sensitivity) was 0.85. Conclusion Predicting difficult laryngoscopy is possible with three parameters. Severe damage resulting from failure to predict difficult laryngoscopy with high recall is small with the reported model. The model’s performance can be further enhanced by additional data training.

We investigate the surface oxidation in a van der Waals ferromagnet Fe3-xGeTe2, a material widely utilized for spintronic applications. While known for its relative air-insensitivity, exposure to air during the handling process (e.g. device or heterostructure fabrication) can lead to reduction or disappearance of its magnetic signal. Comparison of x-ray absorption and x-ray magnetic circular dichroism spectra between pristine and air-exposed Fe3-xGeTe2 confirm a naturally oxidized surface layer on the material. The surface oxide layer has predominantly Fe3+ content. X-ray absorption spectroscopy done on micron-sized exfoliated Fe3-xGeTe2 flakes reveal that the change in the surface chemical properties can be quite significant for thin flakes. The surface modulation of Fe3-xGeTe2 can lead to inaccuracies in characterizing its interfacial magnetic and spin transport properties, and complicate device and heterostructure fabrication processes.

The induced Pt magnetization in a Pt/Co/Pt thin film structure is studied. The normally nonmagnetic Pt acquires a magnetic moment due to the magnetic proximity effect at the Co–Pt interfaces. Element specific Pt structural and magnetic properties are characterized by synchrotron-based resonant x-ray reflectivity and x-ray resonant magnetic reflectivity measurements. An advanced analysis method based on Bayesian inference is used for model fitting of the x-ray data. Using this method, we retrieve the best fit values of material parameters (e.g., thickness, interfacial roughness) from the data. Analysis of x-ray reflectivity data of this specific system shows that the Pt magnetization and Co–Pt interfacial roughness is significantly different between the top and bottom Pt layers, with both values being larger in the top Pt. The successful application of this Bayesian method to study the magnetic and structural properties of a thin film system demonstrates its effectiveness for x-ray reflectivity data analysis.

Purpose: The final purpose of this study is to minimize the cost and time required in the green remodeling decision making and further promote the green remodeling market, and in this work, a standard model for each type of public building was developed as a first step to develop judgement tools to support pre-decision making. Method: The standard model refers to a series of databases with pre-set input variables for each type of building in order to minimize existing complex energy simulation input variables and increase accessibility to non-specialists. The database was established using existing public building licensing data, building energy efficiency certification cases, legal standards, and related research. Result: Based on the standard model database, we will develop support tools for pre-decision making of green remodeling and develop a web-based system that can easily compare energy requirements before and after green remodeling improvement and calculate expected construction costs.

Searching for the ground state of a given system is one of the most fundamental and classical questions in scientific research fields. However, when the system is complex and large, it often becomes an intractable problem; there is essentially no possibility of finding a global energy minimum state with reasonable computational resources. Recently, a novel method based on deep learning techniques was devised as an innovative optimization method to estimate the ground state. We apply this method to one of the most complicated spin-ice systems, aperiodic Penrose P3 patterns. From the results, we discover new configurations of topologically induced emergent frustrated spins, different from those previously known. Additionally, a candidate of the ground state for a still unexplored type of Penrose P3 spin-ice system is first proposed through this study. We anticipate that the capabilities of the deep learning techniques will not only improve our understanding on the physical properties of artificial spin-ice systems, but also bring about significant advances in a wide range of scientific research fields requiring computational approaches for optimization.

Nanoscale-layered ferromagnets have demonstrated fascinating two-dimensional magnetism down to atomic layers, providing a peculiar playground of spin orders for investigating fundamental physics an...

van der Waals (vdW) magnetic materials provide an ideal platform to study low-dimensional magnetism. However, observations of magnetic characteristics of these layered materials truly distinguishing them from conventional magnetic thin film systems have been mostly lacking. In an effort to investigate magnetic properties unique to vdW magnetic materials, we examine the exchange bias effect, a magnetic phenomenon emerging at the ferromagnetic-antiferromagnetic interface. Exchange bias is observed in the naturally oxidized vdW ferromagnet Fe3GeTe2, owing to an antiferromagnetic ordering in the surface oxide layer. Interestingly, the magnitude and thickness dependence of the effect is unlike those expected in typical thin-film systems. We propose a possible mechanism for this behavior, based on the weak interlayer magnetic coupling inherent to vdW magnets, demonstrating the distinct properties of these materials. Furthermore, the robust and sizable exchange bias for vdW magnets persisting up to relatively high temperatures presents a significant advance for realizing practical two-dimensional spintronics.

Skrymions are topological spin textures in chiral magnetic materials and can provide new possibilities for next-generation devices. Real-space Berry curvature can play an important role in controlling the motion of skrymions. Here, we introduce ways to measure Dzyaloshinskii–Moriya interaction, which is closely related to the formation of skrymions, and to determine atomic positions by using X-ray scattering. We also review brief studies on skyrmions in two-dimensional (2D) magnetic heterostructures and the Moiré of van der Waals 2D magnets.

A controversy arose over the interpretation of the recently observed hump features in Hall resistivity ρ x y from ultra-thin SrRuO3 (SRO) film; it was initially interpreted to be due to topological Hall effect but was later proposed to be from existence of regions with different anomalous Hall effect (AHE). In order to settle down the issue, we performed Hall effect as well as magneto-optic Kerr-effect measurements on 4 unit cell SRO films. Clear hump features are observed in ρ x y , whereas neither hump feature nor double hysteresis loop is seen in the Kerr rotation which should be proportional to the magnetization. In addition, magnetization measurement by superconducting quantum interference device shows no sign of multiple coercive fields. These results show that inhomogeneous AHE alone cannot explain the observed hump behavior in ρ x y data. We suggest that emergence of the hump structure in ρ x y is closely related to the growth condition.

Identifying material parameters affecting properties of ferromagnets is key to optimized materials that are better suited for spintronics. Magnetic anisotropy is of particular importance in van der Waals magnets, since it not only influences magnetic and spin transport properties, but also is essential to stabilizing magnetic order in the two-dimensional limit. Here, we report that hole doping effectively modulates the magnetic anisotropy of a van der Waals ferromagnet and explore the physical origin of this effect. Fe3-xGeTe2 nanoflakes show a significant suppression of the magnetic anisotropy with hole doping. Electronic structure measurements and calculations reveal that the chemical potential shift associated with hole doping is responsible for the reduced magnetic anisotropy by decreasing the energy gain from the spin-orbit induced band splitting. Our findings provide an understanding of the intricate connection between electronic structures and magnetic properties in two-dimensional magnets and propose a method to engineer magnetic properties through doping.

The properties of complicated magnetic domain structures induced by various spin–spin interactions in magnetic systems have been extensively investigated in recent years. To understand the statistical and dynamic properties of complex magnetic structures, it is crucial to obtain information on the effective field distribution over the structure, which is not directly provided by magnetization. In this study, we use a deep learning technique to estimate the effective fields of spin configurations. We construct a deep neural network and train it with spin configuration datasets generated by Monte Carlo simulation. We show that the trained network can successfully estimate the magnetic effective field even though we do not offer explicit Hamiltonian parameter values. The estimated effective field information is highly applicable; it is utilized to reduce noise, correct defects in the magnetization data, generate spin configurations, estimate external field responses, and interpret experimental images.

Numerical generation of physical states is essential to all scientific research fields. The role of a numerical generator is not limited to understanding experimental results; it can also be employed to predict or investigate characteristics of uncharted systems. A variational autoencoder model is devised and applied to a magnetic system to generate energetically stable magnetic states with low local deformation. The spin structure stabilization is made possible by taking the explicit magnetic Hamiltonian into account to minimize energy in the training process. A significant advantage of the model is that the generator can create a long‐range ordered ground state of spin configuration by increasing the role of stabilization even if the ground states are not necessarily included in the training process. It is expected that the proposed Hamiltonian‐guided generative model can bring about great advances in numerical approaches used in various scientific research fields., An energy‐minimization variational autoencoder model is devised to generate energetically stable physical states by taking the explicit Hamiltonian into the training process. A significant advantage of the model is that the generator can produce the ground states of various systems even if the ground states are not necessarily included in the training process.

Background Alopecia refers to a condition developed by gradual reduction of hair loss by various abnormal causes such as endocrine system, genetic factors, and stress. Stromal vascular fraction (SVF) isolated from the fat is one of the latest innovative solutions in the field of regeneration therapy. We focused on presenting effectiveness of clinical cases to improve AGA through transplantation of autologous SVF into the scalp. Objective To confirm the efficacy of the autologous SVF usage to the patients with AGA. Methods Nine patients (age range 43–64 years; 4 men, grade IV to V and 5 women, grade I to III), who are suffering from androgenic alopecia (AGA), were treated with single transplantation of autologous SVF in the upper scalp. Autologous SVF was isolated and characterized prior to the injection of live 7–9 × 106 cells into the patients’ treatment site. The hair loss improvement effect was assessed by three test criteria: hair skin quality, hair thickness and hair density 3 and 6 months after post-injection compared to pre-injection status. Results Hair density of SVF-treated side was significantly increased after 3 and 6 months of transplantation compared to non-treated side (P = 0.01 and P = 0.009 per each). And significant improvement in the score of the keratin on the scalp was seen in the injected area as compared to the non-injected area 6 months after transplantation (P = 0.032). Although thickness increase was observed at 3 and 6 months after transplantation, there was no statistical significance (P = 0.142 and 0.155, respectively). Conclusions One transplantation of autologous SVF for the AGA patients, hair density and score for the keratin were significantly increased within 6 months. This study shows that SVF is a very effective way to treat hair loss and most of subjects are satisfied with the result after treatment.

The low-field sensitivity of a giant magnetoresistance (GMR) spin valve can be enhanced by tailoring the bias field of the free layer because this sensitivity and bias field are known to show a strong correlation. In this study, the free-layer bias field is reduced considerably to almost zero via the insertion of an ultrathin nonmagnetic spacer between the pinned layer and the pinning layer. The spacer promotes an increase in the density of Néel walls in the pinned layer. This increase, in turn, induces domain-wall-induced magnetostatic interactions of the free poles formed on the Néel walls inside the free and pinned layers. The magnetostatic interactions result in the formation of flux closures that act as pinning sites during the magnetization reversal process and stabilize the antiparallel magnetization state between the free layer and the pinned layer by suppressing the switching of the free layer from the antiparallel state to the parallel state. Furthermore, the spacer offers an additional advantage of increasing the GMR ratio by inducing a specular scattering effect at its top and bottom interfaces. A highly improved low-field sensitivity of 12.01 mV/mA·Oe is achieved in the sample with a Cu/Pt dual spacer.

The electric field-induced modifications of magnetic anisotropy in CoFeB/MgO systems are studied using X-ray resonant magnetic scattering and magneto-optical Kerr effect. Voltage dependent changes of the magnetic anisotropy of −12.7 fJ/Vm and −8.32 fJ/Vm are observed for Ta/CoFeB/MgO and Hf/CoFeB/MgO systems, respectively. This implies that the interfacial perpendicular magnetic anisotropy is reduced (enhanced) when electron density is increased (decreased). X-ray resonant magnetic scattering measurements reveal that the small in-plane magnetic component of the remanent state of CoFeB/MgO systems with weak magnetic anisotropy changes depending on the applied voltage leading to modification of the magnetic anisotropy at the CoFeB/MgO interface.

van der Waals (vdW) magnetic materials provide an ideal platform to study low-dimensional magnetism. However, observations of magnetic characteristics of these layered materials truly distinguishing them from conventional magnetic thin film systems have been mostly lacking. In an effort to investigate magnetic properties unique to vdW magnetic materials, we examine the exchange bias effect, a magnetic phenomenon emerging at the ferromagnetic-antiferromagnetic interface. Exchange bias is observed in the naturally oxidized vdW ferromagnet Fe

Investigating the effects of the complex magnetic interactions on the formation of nontrivial magnetic phases enables a better understanding of magnetic materials. Moreover, an effective method to systematically control those interactions and phases could be extensively utilized in spintronic devices. SrRuO3 heterostructures function as a suitable material system to investigate the complex magnetic interactions and the resultant formation of topological magnetic phases, as the heterostructuring approach provides an accessible controllability to modulate the magnetic interactions. In this study, we have observed that the Hall effect of SrRuO3/SrTiO3 superlattices varies nonmonotonically with the repetition number (z). Using Monte Carlo simulations, we identify a possible origin of this experimental observation: the interplay between the Dzyaloshinskii-Moriya interaction and dipole-dipole interaction, which have differing z-dependence, might result in a z-dependent modulation of topological magnetic phases. This approach provides not only a collective understanding of the magnetic interactions in artificial heterostructures but also a facile control over the skyrmion phases., Comment: 3 figures

BackgroundIn patients with massive bleeding during surgery, the effect of intra- and postoperative fluid and blood volume on postoperative pulmonary edema is uncertain. The aim of this study is evaluating the occurrence risk relationship through time-varying analysis between postoperative pulmonary edema and intra- and postoperatively administered volume of fluid and blood in patients with intraoperative massive bleeding.MethodsThis study is a retrospective cohort study and data was obtained from the clinical data warehouse at Hallym University Medical Center, a multi-institutional data registry of 5 hospitals of Hallym University. Patients with intraoperative massive bleeding (≥40% of average blood volume) and who underwent a non-cardiac surgery at 5 hospitals between January 1, 2010, and December 31, 2019 were enrolled the study. The primary outcome was postoperative pulmonary edema occurrence within 72 hours after surgery. Secondary outcomes were postoperative pulmonary edema with hypoxemia. ResultsIn total, 2090 patients were included in the postoperative pulmonary edema analysis, and 300 patients developed pulmonary edema within 72 hours after surgery. The postoperative pulmonary edema hypoxemia analysis with hypoxia included 1660 patients; pulmonary edema with hypoxemia occurred in 161 patients. The increase in the amount of red blood cells/average blood volume/hour after surgery increased the risk of developing pulmonary edema after surgery (hazard ratio: 1.03, 95% confidence interval [1.01–1.05], P = 0.013) and the risk of developing pulmonary edema with hypoxemia (hazard ratio: 1.04, 95% confidence interval [1.01–1.07], P = 0.024).Conclusion In this study, an increase in the transfusion of red blood cells per hour after surgery increased the risk of developing pulmonary edema after surgery. This increase can be considered a risk factor for the incidence of pulmonary edema.

Autoencoder , an artificial neural network , was adopted to generate spin structures that interpolate and extrapolate between two distinct magnetic chiral states, the labyrinth structure and the skyrmion structure. We trained the autoencoder using two distinct magnetic chiral structures. Each input data is encoded through a deep learning process into a latent code, a new representation of the information in a reduced dimensional space. We investigated the latent space to acquire information on the structure of the latent code distribution. With the acquired information, we successfully produced various magnetic structures that exhibit plausible properties under various external fields not provided in the training data. The latent codes were modified by two algorithms. The first algorithm utilizes inversion and translation operation in the latent space and the second algorithm uses recursive flow with a modification bias. The first produced structures preserving the chiral structure of original data and the second produced statistically plausible states.

Thus far, few studies have compared the effects of sugammadex and cholinesterase inhibitors on postoperative nausea and vomiting (PONV), and the results have been controversial. Here, we compared the effects of sugammadex, neostigmine, and pyridostigmine on PONV by means of a five hospital analysis with propensity score matching. We analyzed adults aged &ge, 18 years who underwent general anesthesia between January 2014 and December 2019. Following propensity score matching, 7793 patients were included in each of the neostigmine and sugammadex matched patient groups (absolute standardized difference (ASD), 0.01&ndash, 0.07), and 10,197 patients were included in each of the pyridostigmine and sugammadex matched patient groups (ASD, 0.01&ndash, 0.02), while 19,377 patients were included in each of the pyridostigmine and neostigmine matched patient groups. (ASD, 0.01&ndash, 0.19). The odds of PONV were low in the sugammadex group (odds ratio, 0.65, 95% confidence interval, 0.59&ndash, 0.72, p &lt, 0.0001) and pyridostigmine group (odds ratio, 0.22, 95% confidence interval, 0.20&ndash, 0.24, 0.0001) compared to the neostigmine group, while there was no difference between sugammadex and pyridostigmine (odds ratio, 0.95, 95% confidence interval, 0.86&ndash, 1.04, p = 0.281). Therefore, sugammadex and pyridostigmine may lower the incidence of PONV compared to neostigmine in patients undergoing general anesthesia.

Understanding spin textures in magnetic systems is extremely important to the spintronics and it is vital to extrapolate the magnetic Hamiltonian parameters through the experimentally determined spin. It can provide a better complementary link between theories and experimental results. We demonstrate deep learning can quantify the magnetic Hamiltonian from magnetic domain images. To train the deep neural network, we generated domain configurations with Monte Carlo method. The errors from the estimations was analyzed with statistical methods and confirmed the network was successfully trained to relate the Hamiltonian parameters with magnetic structure characteristics. The network was applied to estimate experimentally observed domain images. The results are consistent with the reported results, which verifies the effectiveness of our methods. On the basis of our study, we anticipate that the deep learning techniques make a bridge to connect the experimental and theoretical approaches not only in magnetism but also throughout any scientific research.

Néel-type skyrmions in van der Waals ferromagnetic Fe3GeTe2 on (Co/Pd)n superlattice were created without external magnetic field., Magnetic skyrmions are topological spin textures, which usually exist in noncentrosymmetric materials where the crystal inversion symmetry breaking generates the so-called Dzyaloshinskii-Moriya interaction. This requirement unfortunately excludes many important magnetic material classes, including the recently found two-dimensional van der Waals (vdW) magnetic materials, which offer unprecedented opportunities for spintronic technology. Using photoemission electron microscopy and Lorentz transmission electron microscopy, we investigated and stabilized Néel-type magnetic skyrmion in vdW ferromagnetic Fe3GeTe2 on top of (Co/Pd)n in which the Fe3GeTe2 has a centrosymmetric crystal structure. We demonstrate that the magnetic coupling between the Fe3GeTe2 and the (Co/Pd)n could create skyrmions in Fe3GeTe2 without the need of an external magnetic field. Our results open exciting opportunities in spintronic research and the engineering of topologically protected nanoscale features by expanding the group of skyrmion host materials to include these previously unknown vdW magnets.

Exploiting spin transport increases the functionality of electronic devices and enables such devices to overcome physical limitations related to speed and power. Utilizing the Rashba effect at the interface of heterostructures provides promising opportunities toward the development of high-performance devices because it enables electrical control of the spin information. Herein, the focus is mainly on progress related to the two most compelling devices that exploit the Rashba effect: spin transistors and spin-orbit torque devices. For spin field-effect transistors, the gate-voltage manipulation of the Rashba effect and subsequent control of the spin precession are discussed, including for all-electric spin field-effect transistors. For spin-orbit torque devices, recent theories and experiments on interface-generated spin current are discussed. The future directions of manipulating the Rashba effect to realize fully integrated spin logic and memory devices are also discussed.

Postoperative nausea and vomiting (PONV) are common complications after anesthesia, but no study has considered the effects of a proton pump inhibitor (PPI) and gastroesophageal reflux disease (GERD) on PONV at the same time. Thus, we investigated the effects of a PPI and GERD on PONV. Patients aged &ge, 18 years who underwent general anesthesia between 2010 and 2019 were enrolled. In total, 202,439 patients were included and 21,361 In a multivariate analysis, the OR for PONV was higher in subjects with GERD (OR, 1.157, 95% CI, 1.032&ndash, 1.298, p = 0.012). The OR was lower for subjects with taking a PPI (OR, 0.890, 95% CI, 0.832&ndash, 0.953, p &lt, 0.0001). In patients without GERD, the incidence of PONV was lower when lansoprazole (OR, 0.801, 95% CI, 0.718&ndash, 0.894, 0.0001), pantoprazole (OR, 0.856, 95% CI, 0.748&ndash, 0.980, p = 0.025) and ilaprazole (OR, 0.391, 95% CI, 0.158&ndash, 0.966, p = 0.042) were taken. However, in GERD patients, all PPIs did not show reducing the incidence of PONV. Taken together, the results show that a lansoprazole, pantoprazole, and ilaprazole reduced PONV in patients without GERD, and PPI could not reduce PONV in patients with GERD.

Current-induced magnetic domain wall (DW) motion is an important operating principle of spintronic devices. Injected current generates spin torques (STs) on the DWs in two ways. One is the spin transfer from magnetic domains to the walls by the current flowing in the magnet. Current flow in attached heavy metals also generates another ST because of the spin-Hall effect. Both phenomena explain the wall motions well; therefore, their respective contribution is an important issue. Here, we show the simultaneous measurement of both torques by using magnetic facet domains that form mountain-shaped domains with straight walls. When the STs and the external magnetic field push the walls in opposite directions, the walls should have equilibrium angles to create balanced states. Such angles can be modulated by an additional in-plane magnetic field. Angle measurements distinguish the STs because each torque has a distinct mechanism related to the DW structure.

Merons which are topologically equivalent to one-half of skyrmions can exist only in pairs or groups in two-dimensional (2D) ferromagnetic (FM) systems. The recent discovery of meron lattice in chiral magnet Co8Zn9Mn3 raises the immediate challenging question that whether a single meron pair, which is the most fundamental topological structure in any 2D meron systems, can be created and stabilized in a continuous FM film? Utilizing winding number conservation, we develop a new method to create and stabilize a single pair of merons in a continuous Py film by local vortex imprinting from a Co disk. By observing the created meron pair directly within a magnetic field, we determine its topological structure unambiguously and explore the topological effect in its creation and annihilation processes. Our work opens a pathway towards developing and controlling topological structures in general magnetic systems without the restriction of perpendicular anisotropy and Dzyaloshinskii–Moriya interaction., A meron is one half of a skyrmion but whether a single meron pair can be created and stabilized remains a challenging question. Here, Gao et al. develop a method to create and stabilize individual pairs of merons in a continuous Py film by local vortex imprinting from Co disks.

Identifying material parameters affecting properties of ferromagnets is key to optimized materials that are better suited for spintronics. Magnetic anisotropy is of particular importance in van der Waals magnets, since it not only influences magnetic and spin transport properties, but also is essential to stabilizing magnetic order in the two-dimensional limit. Here, we report that hole doping effectively modulates the magnetic anisotropy of a van der Waals ferromagnet and explore the physical origin of this effect. Fe

We propose a new efficient algorithm to simulate magnetic structures numerically. It contains a generative model using a complex-valued neural network to generate k-space information. The output information is hermitized and transformed into real-space spin configurations through an inverse fast Fourier transform. The Adam version of stochastic gradient descent is used to minimize the magnetic energy, which is the cost of our algorithm. The algorithm provides the proper ground spin configurations with outstanding performance. In model cases, the algorithm was successfully applied to solve the spin configurations of magnetic chiral structures. The results also showed that a magnetic long-range order could be obtained regardless of the total simulation system size.

Using Monte-Carlo simulations and micromagnetic simulations, we reveal how the spin structural correlation and the skyrmion dynamics are affected by the interlayer coupling in a chiral magnetic bilayer system, in which the two layers have opposite chirality. The interaction through interlayer coupling between chiral magnetic structures influences the static and dynamics properties profoundly. The competition between the Dzyaloshinskii-Moriya interaction and the interlayer interaction allows multiple magnetic structures to be energetically stable, which includes sole skyrmion states (skyrmion appears in only one of the layers) and skyrmion pair states (coupled skyrmions in top and bottom layers). When current driven spin transfer torques are applied to each state, the sole skyrmion state is mainly propelled by a spin transfer torque causing the skyrmion hall effect, but the skyrmion pair state is propelled by a torque from skyrmion-skyrmion interaction and not influenced by the skyrmion hall effect. Also upon application of an external magnetic field, we found the skyrmions in a skyrmion pair state extinguish in an exclusive way, as the annihilation of a skyrmion in one of the layers stabilizes the once paired skyrmion in the other layer, i.e. the skyrmion lattice sites have only one skyrmion in either layer.

The depth-resolved magnetic configuration of a Ga0.97Mn0.03As/GaAs:Be multilayer with an antiferromagnetic interlayer exchange coupling was investigated using surface-sensitive soft x-ray resonant magnetic reflectivity (XRMR). We observed intriguing opposite increments in the XRMR intensities at the half-Bragg peak position between two different remanent states with opposite field sweep directions. A quantitative analysis shows that these opposite intensity increments result from two different anti-parallel spin configurations in such a way that the magnetization of top-most magnetic layer is pinned along the saturation magnetization direction before the remanent state. This surface pinning effect is important for understanding spin-dependent transport in semiconducting magnetic multilayers.