Risk factors for ischemic stroke and transient ischemic attack in patients under age 50

To analyze risk factors for ischemic stroke and transient ischemic attack (TIA) in young adults under the age of 50. To make recommendations for additional research and practical consequences. From 97 patients with ischemic stroke or TIA under the age of 50, classical cardiovascular risk factors, coagulation disorders, history of migraine, use of oral contraceptives, cardiac abnormalities on ECG and echocardiography, and the results of duplex ultrasound were retrospectively analyzed. Literature was reviewed and compared to the results. 56.4% of the patients had hypertension, 12.1% increased total cholesterol, 20% hypertriglyceridemia, 31.5% an increased LDL-level, 32.6% a decreased HDL-level and 7.2% a disturbed glucose tolerance. Thrombophilia investigation was abnormal in 21 patients and auto-immune serology was abnormal in 15 patients. Ten of these patients were already known with a systemic disease associated with an increased risk for ischemic stroke (i.e. systemic lupus erythematosus). The ECG was abnormal in 16.7% of the cases, the echocardiography in 12.1% and duplex ultrasound of the carotid arteries was in 31.8% of the cases abnormal. Conventional cardiovascular risk factors are not only important in patients over the age of 50 with ischemic stroke or TIA, but also in this younger population under the age of 50. Thrombophilia investigation and/ or autoimmune serology should be restricted to patients without conventional cardiovascular risk factors and a history or other clinical symptoms associated with hypercoagulability and/ or autoimmune diseases

Field-induced domain wall propagation velocity in magnetic nanowires

A thory of field-induced domain wall (DW) propagation is developed. The theory not only explains why a DW in a defect-free nanowire must propagate at a finite velocity, but also provides a proper definition of DW propagation velocity. This definition, valid for an arbitrary DW structure, allows one to compute the instantaneous DW velocity in a meaningful way even when the DW is not moving as a rigid body. A new velocity-field formula beyond the Walker breakdown field, which is in excellent agreement with both experiments and numerical simulations, is derived

Theory of Current-Driven Domain Wall Motion: A Poorman's Approach

A self-contained theory of the domain wall dynamics in ferromagnets under finite electric current is presented. The current is shown to have two effects; one is momentum transfer, which is proportional to the charge current and wall resistivity (\rhow), and the other is spin transfer, proportional to spin current. For thick walls, as in metallic wires, the latter dominates and the threshold current for wall motion is determined by the hard-axis magnetic anisotropy, except for the case of very strong pinning. For thin walls, as in nanocontacts and magnetic semiconductors, the momentum-transfer effect dominates, and the threshold current is proportional to \Vz/\rhow, \Vz being the pinning potential

Transfer Learning for Domain Adaptation in MRI: Application in Brain Lesion Segmentation

Magnetic Resonance Imaging (MRI) is widely used in routine clinical diagnosis and treatment. However, variations in MRI acquisition protocols result in different appearances of normal and diseased tissue in the images. Convolutional neural networks (CNNs), which have shown to be successful in many medical image analysis tasks, are typically sensitive to the variations in imaging protocols. Therefore, in many cases, networks trained on data acquired with one MRI protocol, do not perform satisfactorily on data acquired with different protocols. This limits the use of models trained with large annotated legacy datasets on a new dataset with a different domain which is often a recurring situation in clinical settings. In this study, we aim to answer the following central questions regarding domain adaptation in medical image analysis: Given a fitted legacy model, 1) How much data from the new domain is required for a decent adaptation of the original network?; and, 2) What portion of the pre-trained model parameters should be retrained given a certain number of the new domain training samples? To address these questions, we conducted extensive experiments in white matter hyperintensity segmentation task. We trained a CNN on legacy MR images of brain and evaluated the performance of the domain-adapted network on the same task with images from a different domain. We then compared the performance of the model to the surrogate scenarios where either the same trained network is used or a new network is trained from scratch on the new dataset.The domain-adapted network tuned only by two training examples achieved a Dice score of 0.63 substantially outperforming a similar network trained on the same set of examples from scratch.Comment: 8 pages, 3 figure

Parameterization of oceanic whitecap fraction based on satellite observations

In this study, the utility of satellite-based white-cap fraction (W) data for the prediction of sea spray aerosol (SSA) emission rates is explored. More specifically, the study aims at evaluating how an account for natural variability of whitecaps in the W parameterization would affect SSA mass flux predictions when using a sea spray source function (SSSF) based on the discrete whitecap method. The starting point is a data set containing W data for 2006 together with matching wind speed U-10 and sea surface temperature (SST) T. Whitecap fraction W was estimated from observations of the ocean surface brightness temperature T-B by satellite-borne radiometers at two frequencies (10 and 37 GHz). A global-scale assessment of the data set yielded approximately quadratic correlation between W and U-10. A new global W(U-10) parameterization was developed and used to evaluate an intrinsic correlation between W and U-10 that could have been introduced while estimating W from T B. A regional-scale analysis over different seasons indicated significant differences of the coefficients of regional W(U-10) relationships. The effect of SST on W is explicitly accounted for in a new W(U-10, T) parameterization. The analysis of W values obtained with the new W(U-10) and W(U-10, T) parameterizations indicates that the influence of secondary factors on W is for the largest part embedded in the exponent of the wind speed dependence. In addition, the W(U-10, T) parameterization is able to partially model the spread (or variability) of the satellite-based W data. The satellite-based parameterization W(U-10, T) was applied in an SSSF to estimate the global SSA emission rate. The thus obtained SSA production rate for 2006 of 4.4 x 10(12) kg year(-1) is within previously reported estimates, however with distinctly different spatial distribution.Peer reviewe

The Quantum Affine Origin of the AdS/CFT Secret Symmetry

We find a new quantum affine symmetry of the S-matrix of the one-dimensional Hubbard chain. We show that this symmetry originates from the quantum affine superalgebra U_q(gl(2|2)), and in the rational limit exactly reproduces the secret symmetry of the AdS/CFT worldsheet S-matrix.Comment: 22 page

The Bethe Ansatz for AdS5 x S5 Bound States

We reformulate the nested coordinate Bethe ansatz in terms of coproducts of Yangian symmetry generators. This allows us to derive the nested Bethe equations for the bound state string S-matrices. We find that they coincide with the Bethe equations obtained from a fusion procedure. The bound state number dependence in the Bethe equations appears through the parameters x^{\pm} and the dressing phase only.Comment: typos correcte

Contour deformation trick in hybrid NLIE

The hybrid NLIE of AdS_5 x S^5 is applied to a wider class of states. We find that the Konishi state of the orbifold AdS_5 x (S^5/Z_S) satisfies A_1 NLIE with the source terms which are derived from contour deformation trick. For general states, we construct a deformed contour with which the contour deformation trick yields the correct source terms.Comment: 39 pages, 6 figures, v2: discussion on analyticity constraints replaced by consistent deformed contou

Obesity and its impact on COVID-19

The severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) pandemic has proven a challenge to healthcare systems since its first appearance in late 2019. The global spread and devastating effects of coronavirus disease 2019 (COVID-19) on patients have resulted in countless studies on risk factors and disease progression. Overweight and obesity emerged as one of the major risk factors for developing severe COVID-19. Here we review the biology of coronavirus infections in relation to obesity. In particular, we review literature about the impact of adiposity-related systemic inflammation on the COVID-19 disease severity, involving cytokine, chemokine, leptin, and growth hormone signaling, and we discuss the involvement of hyperactivation of the renin-angiotensin-aldosterone system (RAAS). Due to the sheer number of publications on COVID-19, we cannot be completed, and therefore, we apologize for all the publications that we do not cite

Reproducible resistive switching in nonvolatile organic memories

Resistive switching in nonvolatile, two terminal organic memories can be due to the presence of a native oxide layer at an aluminum electrode. Reproducible solid state memories can be realized by deliberately adding a thin sputtered Al2O3 layer to nominal electron-only, hole-only, and bipolar organic diodes. Before memory operation, the devices have to be formed at an electric field of 10(9) V/m, corresponding to soft breakdown of Al2O3. After forming, the structures show pronounced negative differential resistance and the local maximum in the current scales with the thickness of the oxide layer. The polymer acts as a current limiting series resistance