Initial-state effects in scanned-energy-mode photoelectron diffraction

By a combination of experimental data [from the Ni (111) (2×2)-K structure], model calculations, and simple formal theory, it shown that a strong initial-state effect exists in backscattering photoelectron diffraction, which can be ascribed to the parity of the emitted photoelectron source wave field. Unlike the initial-state effect recently discussed in forward scattering photoelectron (and Auger electron) diffraction, which is a spherical wave effect only present due to the close proximity of the emitter and scatterer, this parity effect in the backscattering geometry exists even in the lowest order approximation of the scattering, i.e. the plane wave approximation

A scalable neural network architecture for self-supervised tomographic image reconstruction

We present a lightweight and scalable artificial neural network architecture which is used to reconstruct a tomographic image from a given sinogram. A self-supervised learning approach is used where the network iteratively generates an image that is then converted into a sinogram using the Radon transform; this new sinogram is then compared with the sinogram from the experimental dataset using a combined mean absolute error and structural similarity index measure loss function to update the weights of the network accordingly. We demonstrate that the network is able to reconstruct images that are larger than 1024 × 1024. Furthermore, it is shown that the new network is able to reconstruct images of higher quality than conventional reconstruction algorithms, such as the filtered back projection and iterative algorithms (SART, SIRT, CGLS), when sinograms with angular undersampling are used. The network is tested with simulated data as well as experimental synchrotron X-ray micro-tomography and X-ray diffraction computed tomography data

A Novel Long Range Spin Chain and Planar N=4 Super Yang-Mills

We probe the long-range spin chain approach to planar N=4 gauge theory at high loop order. A recently employed hyperbolic spin chain invented by Inozemtsev is suitable for the SU(2) subsector of the state space up to three loops, but ceases to exhibit the conjectured thermodynamic scaling properties at higher orders. We indicate how this may be bypassed while nevertheless preserving integrability, and suggest the corresponding all-loop asymptotic Bethe ansatz. We also propose the local part of the all-loop gauge transfer matrix, leading to conjectures for the asymptotically exact formulae for all local commuting charges. The ansatz is finally shown to be related to a standard inhomogeneous spin chain. A comparison of our ansatz to semi-classical string theory uncovers a detailed, non-perturbative agreement between the corresponding expressions for the infinite tower of local charge densities. However, the respective Bethe equations differ slightly, and we end by refining and elaborating a previously proposed possible explanation for this disagreement.Comment: 48 pages, 1 figure. v2, further results added: discussion of the relationship to an inhomogeneous spin chain, normalization in sec 3 unified, v3: minor mistakes corrected, published versio

Automated final lesion segmentation in posterior circulation acute ischemic stroke using deep learning

Final lesion volume (FLV) is a surrogate outcome measure in anterior circulation stroke (ACS). In posterior circulation stroke (PCS), this relation is plausibly understudied due to a lack of methods that automatically quantify FLV. The applicability of deep learning approaches to PCS is limited due to its lower incidence compared to ACS. We evaluated strategies to develop a convolutional neural network (CNN) for PCS lesion segmentation by using image data from both ACS and PCS patients. We included follow-up non-contrast computed tomography scans of 1018 patients with ACS and 107 patients with PCS. To assess whether an ACS lesion segmentation generalizes to PCS, a CNN was trained on ACS data (ACS-CNN). Second, to evaluate the performance of only including PCS patients, a CNN was trained on PCS data. Third, to evaluate the performance when combining the datasets, a CNN was trained on both datasets. Finally, to evaluate the performance of transfer learning, the ACS-CNN was fine-tuned using PCS patients. The transfer learning strategy outperformed the other strategies in volume agreement with an intra-class correlation of 0.88 (95% CI: 0.83–0.92) vs. 0.55 to 0.83 and a lesion detection rate of 87% vs. 41–77 for the other strategies. Hence, transfer learning improved the FLV quantification and detection rate of PCS lesions compared to the other strategies

MR CLEAN-LATE, a multicenter randomized clinical trial of endovascular treatment of acute ischemic stroke in The Netherlands for late arrivals:study protocol for a randomized controlled trial

BACKGROUND: Endovascular therapy (EVT) for acute ischemic stroke due to proximal occlusion of the anterior intracranial circulation, started within 6 h from symptom onset, has been proven safe and effective. Recently, EVT has been proven effective beyond the 6-h time window in a highly selected population using CT perfusion or MR diffusion. Unfortunately, these imaging modalities are not available in every hospital, and strict selection criteria might exclude patients who could still benefit from EVT. The presence of collaterals on CT angiography (CTA) may offer a more pragmatic imaging criterion that predicts possible benefit from EVT beyond 6 h from time last known well. The aim of this study is to assess the safety and efficacy of EVT for patients treated between 6 and 24 h from time last known well after selection based on the presence of collateral flow. METHODS: The MR CLEAN-LATE trial is a multicenter, randomized, open-label, blinded endpoint trial, aiming to enroll 500 patients. We will investigate the efficacy of EVT between 6 and 24 h from time last known well in acute ischemic stroke due to a proximal intracranial anterior circulation occlusion confirmed by CTA or MRA. Patients with any collateral flow (poor, moderate, or good collaterals) on CTA will be included. The inclusion of poor collateral status will be restricted to a maximum of 100 patients. In line with the current Dutch guidelines, patients who fulfill the characteristics of included patients in DAWN and DEFUSE 3 will be excluded as they are eligible for EVT as standard care. The primary endpoint is functional outcome at 90 days, assessed with the modified Rankin Scale (mRS) score. Treatment effect will be estimated with ordinal logistic regression (shift analysis) on the mRS at 90 days. Secondary endpoints include clinical stroke severity at 24 h and 5-7 days assessed by the NIHSS, symptomatic intracranial hemorrhage, recanalization at 24 h, follow-up infarct size, and mortality at 90 days, DISCUSSION: This study will provide insight into whether EVT is safe and effective for patients treated between 6 and 24 h from time last known well after selection based on the presence of collateral flow on CTA. TRIAL REGISTRATION: NL58246.078.17 , ISRCTN19922220 , Registered on 11 December 2017

Thermodynamic Properties of Supported and Embedded Metallic Nanocrystals: Gold on/in SiO2

We report on the calculations of the cohesive energy, melting temperature and vacancy formation energy for Au nanocrystals with different size supported on and embedded in SiO2. The calculations are performed crossing our previous data on the surface free energy of the supported and embedded nanocrystals with the theoretical surface-area-difference model developed by W. H. Qi for the description of the size-dependent thermodynamics properties of low-dimensional solid-state systems. Such calculations are employed as a function of the nanocrystals size and surface energy. For nanocrystals supported on SiO2, as results of the calculations, we obtain, for a fixed nanocrystal size, an almost constant cohesive energy, melting temperature and vacancy formation energy as a function of their surface energy; instead, for those embedded in SiO2, they decreases when the nanocrystal surface free energy increases. Furthermore, the cohesive energy, melting temperature and vacancy formation energy increase when the nanocrystal size increases: for the nanocrystals on SiO2, they tend to the values of the bulk Au; for the nanocrystals in SiO2 in correspondence to sufficiently small values of their surface energy, they are greater than the bulk values. In the case of the melting temperature, this phenomenon corresponds to the experimentally well-known superheating process

Endovascular treatment in anterior circulation stroke beyond 6.5 hours after onset or time last seen well:results from the MR CLEAN Registry

BACKGROUND: Randomised controlled trials with perfusion selection have shown benefit of endovascular treatment (EVT) for ischaemic stroke between 6 and 24 hours after symptom onset or time last seen well. However, outcomes after EVT in these late window patients without perfusion imaging are largely unknown. We assessed their characteristics and outcomes in routine clinical practice. METHODS: The Multicenter Randomized Clinical Trial of Endovascular Treatment for Acute Ischemic Stroke in the Netherlands Registry, a prospective, multicentre study in the Netherlands, included patients with an anterior circulation occlusion who underwent EVT between 2014 and 2017. CT perfusion was no standard imaging modality. We used adjusted ordinal logistic regression analysis to compare patients treated within versus beyond 6.5 hours after propensity score matching on age, prestroke modified Rankin Scale (mRS), National Institutes of Health Stroke Scale, Alberta Stroke Programme Early CT Score (ASPECTS), collateral status, location of occlusion and treatment with intravenous thrombolysis. Outcomes included 3-month mRS score, functional independence (defined as mRS 0–2), and death. RESULTS: Of 3264 patients who underwent EVT, 106 (3.2%) were treated beyond 6.5 hours (median 8.5, IQR 6.9–10.6), of whom 93 (87.7%) had unknown time of stroke onset. CT perfusion was not performed in 87/106 (80.2%) late window patients. Late window patients were younger (mean 67 vs 70 years, p<0.04) and had slightly lower ASPECTS (median 8 vs 9, p<0.01), but better collateral status (collateral score 2–3: 68.3% vs 57.7%, p=0.03). No differences were observed in proportions of functional independence (43.3% vs 40.5%, p=0.57) or death (24.0% vs 28.9%, p=0.28). After matching, outcomes remained similar (adjusted common OR for 1 point improvement in mRS 1.04, 95% CI 0.56 to 1.93). CONCLUSIONS: Without the use of CT perfusion selection criteria, EVT in the 6.5–24-hour time window was not associated with poorer outcome in selected patients with favourable clinical and CT/CT angiography characteristics. randomised controlled trials with lenient inclusion criteria are needed to identify more patients who can benefit from EVT in the late window

Automatic segmentation of cerebral infarcts in follow-up computed tomography images with convolutional neural networks

Background and purpose: Infarct volume is a valuable outcome measure in treatment trials of acute ischemic stroke and is strongly associated with functional outcome. Its manual volumetric assessment is, however, too demanding to be implemented in clinical practice. Objective: To assess the value of convolutional neural networks (CNNs) in the automatic segmentation of infarct volume in follow-up CT images in a large population of patients with acute ischemic stroke. Materials and methods: We included CT images of 1026 patients from a large pooling of patients with acute ischemic stroke. A reference standard for the infarct segmentation was generated by manual delineation. We introduce three CNN models for the segmentati