Undamaged Regions Research Articles

Magnetic imaging of thermally switchable antiferromagnetic/ferromagnetic modulated thin films

Nanoscale magnetic patterning can lead to the formation of a variety of spin textures, depending on the intrinsic properties of the material and the microstructure. Here we report on the spin textures formed in laterally patterned antiferromagnetic (AF)/ferromagnetic (FM) thin film stripes with a period of 200 nm (100 nm FM/100 nm AF). We make use of the AF to FM phase transition in FeRh thin films at ∼100 °C, thereby creating a nanoscale pattern that is thermally switchable between AF/FM stripes and uniformly FM. A combination of spin-resolved photoemission electron microscopy, magnetic force microscopy, and magnetometry measurements allow direct nanoscale observations of the stray magnetic fields emergent from the nanopattern as well as the underlying magnetisation. Our measurements reveal pinning centres resistant to temperature cycling that govern the modulated spin-texture as well as a sub-texture consisting of grain-driven nanoscale magnetisation structure directed out of the film plane. The nanoscale magnetic structure is thus strongly influenced by the film microstructure. Signatures of exchange bias are not observed, most likely due to the small contact area between the AF and FM regions, combined with the fact that the interfaces between the damaged and undamaged regions are likely to be highly diffuse owing to the lateral scattering of incoming ions. These results show that temperature controllable spin textures can be created in FeRh thin films which could find application in domain wall, microwave, or magnonic devices.

Predicting Rail Corrugation Based on Convolutional Neural Networks Using Vehicle's Acceleration Measurements.

This paper presents a deep learning approach for predicting rail corrugation based on on-board rolling-stock vertical acceleration and forward velocity measurements using One-Dimensional Convolutional Neural Networks (CNN-1D). The model's performance is examined in a 1:10 scale railway system at two different forward velocities. During both the training and test stages, the CNN-1D produced results with mean absolute percentage errors of less than 5% for both forward velocities, confirming its ability to reproduce the corrugation profile based on real-time acceleration and forward velocity measurements. Moreover, by using a Gradient-weighted Class Activation Mapping (Grad-CAM) technique, it is shown that the CNN-1D can distinguish various regions, including the transition from damaged to undamaged regions and one-sided or two-sided corrugated regions, while predicting corrugation. In summary, the results of this study reveal the potential of data-driven techniques such as CNN-1D in predicting rails' corrugation using online data from the dynamics of the rolling-stock, which can lead to more reliable and efficient maintenance and repair of railways.

Cooperative nucleic acid binding by Poly ADP-ribose polymerase 1

Poly (ADP)-ribose polymerase 1 (PARP1) is an abundant nuclear protein well-known for its role in DNA repair yet also participates in DNA replication, transcription, and co-transcriptional splicing, where DNA is undamaged. Thus, binding to undamaged regions in DNA and RNA is likely a part of PARP1’s normal repertoire. Here we describe analyses of PARP1 binding to two short single-stranded DNAs, a single-stranded RNA, and a double stranded DNA. The investigations involved comparing the wild-type (WT) full-length enzyme with mutants lacking the catalytic domain (∆CAT) or zinc fingers 1 and 2 (∆Zn1∆Zn2). All three protein types exhibited monomeric characteristics in solution and formed saturated 2:1 complexes with single-stranded T20 and U20 oligonucleotides. These complexes formed without accumulation of 1:1 intermediates, a pattern suggestive of positive binding cooperativity. The retention of binding activities by ∆CAT and ∆Zn1∆Zn2 enzymes suggests that neither the catalytic domain nor zinc fingers 1 and 2 are indispensable for cooperative binding. In contrast, when a double stranded 19mer DNA was tested, WT PARP1 formed a 4:1 complex while the ∆Zn1Zn2 mutant binding saturated at 1:1 stoichiometry. These deviations from the 2:1 pattern observed with T20 and U20 oligonucleotides show that PARP’s binding mechanism can be influenced by the secondary structure of the nucleic acid. Our studies show that PARP1:nucleic acid interactions are strongly dependent on the nucleic acid type and properties, perhaps reflecting PARP1’s ability to respond differently to different nucleic acid ligands in cells. These findings lay a platform for understanding how the functionally versatile PARP1 recognizes diverse oligonucleotides within the realms of chromatin and RNA biology.

Defect detection and localisation using guided wave images from array data processed by nonlinear autoregressive exogenous model and Gamma statistical operator

Guided wave structural health monitoring (GWSHM) systems, using the delay-and-sum imaging algorithm, are an efficient solution to detect and localise defects in industrial structures. However, the image artifacts caused by either imperfect detection or sensor lay-out limitations make it difficult to identify and locate defects accurately. In order to enhance the performance of defect detection and localisation in GWSHM systems, this paper proposes a three-step procedure for post-processing guided wave signals prior to image formation. In the first step, the signals are processed using the nonlinear autoregressive exogenous model to suppress noise from benign features. The second step calculates the probability of defect presence based on the rescaled Gamma cumulative distribution function. This probabilistic threshold is then determined from the quantile mapping. Finally, a guide wave image is formed using the delay-and-sum imaging algorithm. The experimental validation was performed to inspect a 6 mm-diameter through-thickness circular hole on an aluminium plate and the defects were further scaled as simulated datasets to test its detectability under various amplitudes. In the second procedure step, the detection and localisation performance of the proposed procedure was compared with that of using the signal difference coefficient and the Rayleigh maximum likelihood estimator. It is shown that the proposed procedure can enhance the contrast between damaged and undamaged regions, providing more reliable and accurate guided wave images.

Distant neuroinflammation acutely induced by focal brain injury and its control by endocannabinoid system

IntroductionWe studied spatiotemporal features of acute transcriptional inflammatory response induced by a focal brain injury in distant uninjured neuronal tissue and a role of endocannabinoid (eCB) system in its control. Materials and methodsA focal excitotoxic lesion was induced by a unilateral injection of kainate in the dorsal hippocampus of awake Wistar rats. During acute post-injury period (3 h and 24 h post-injection), mRNA levels of genes associated with neuroinflammation (Il1b, Il6, Tnf, Ccl2; Cx3cl1, Zc3 h12a, Tgfb1) and eCB receptors of CB1 and CB2 types (Cnr1 and Cnr2) in intact regions of the hippocampus and neocortex were measured using qPCR. Occurrence of acute symptomatic seizures was controlled electrographically. To modulate eCB signaling during injury and acute post-injury period, antagonists (AM251, AM630) and agonist (WIN55–212-2) of eCB receptors were administered before the injury induction. ResultsLocal intrahippocampal injury triggered widespread time- and region-dependent neuroinflammation in undamaged brain regions remote from the lesion site. The distant areas of the hippocampus and hippocampal meninges exhibited early (3 h) transient upregulation of pro- and anti-inflammatory cytokines simultaneously with occurrence of acute symptomatic seizures. The neocortex and its meninges showed minor neuroinflammation early after injury (3 h) but later (24 h) significantly upregulated several genes, mainly with anti-inflammatory properties. Focal lesion also changed expression of eCB receptors in the distant extra-lesional regions – CB1 receptors at 3 h and both CB1 and CB2 receptors at 24 h. Within the hippocampus, significant regional differences in constitutive and post-injury expression CB1 receptors were found. Pharmacological blockade of eCB receptors during injury and early post-injury period lengthened hippocampal neuroinflammation and reversed upregulation of anti-inflammatory molecules in the neocortex. ConclusionThe findings show that focal brain injury rapidly triggers widespread parenchymal and extraparenchymal neuroinflammation. The early injury-induced response is likely to represent neurogenic neuroinflammation produced by network hyperexcitability (acute symptomatic seizures). Activation of eCB signaling during acute phase of the brain injury is important for initiation of adaptive anti-inflammatory processes and prevention of chronic pathologic neuroinflammation in distant uninjured structures. However, the beneficial role of injury-induced eCB activity appears to depend on many factors including time, brain region, eCB tone etc.

Image inpainting network based on multi‐level attention mechanism

AbstractImage inpainting networks based on deep learning techniques have been widely used in many important fields. However, most inpainting networks fail to generate desirable repaired images. This may be due to their failure to extract effective features and accurately assign high weights to the undamaged regions. To alleviate these problems, an image inpainting network based on gated convolution and multi‐level attention mechanism (IIN‐GCMAM) is proposed in this paper. This network follows encoder–decoder architecture, consisting of the gated convolution encoder (GC‐encoder) and the multi‐level attention mechanism decoder (MAM‐decoder). The GC‐encoder weighs the extracted features with gated convolutions, which reduces the interference caused by the damaged regions. The multi‐level attention mechanism employed in the MAM‐decoder uses multi‐scale feature maps spatially and channel‐wise to improve the consistency in global structure and the fineness of repaired results. Extensive experiments are conducted on the common datasets, Paris StreetView and CelebA. Experimental results indicate that the proposed IIN‐GCMAM can achieve a good performance on the common evaluation metrics and visual effects. It can achieve 0.0408, 0.720, and 22.27 in MAE, SSIM, and PSNR at the mask ratio of 50%–60%, respectively.

PEIPNet: Parametric Efficient Image-Inpainting Network with Depthwise and Pointwise Convolution.

Research on image-inpainting tasks has mainly focused on enhancing performance by augmenting various stages and modules. However, this trend does not consider the increase in the number of model parameters and operational memory, which increases the burden on computational resources. To solve this problem, we propose a Parametric Efficient Image InPainting Network (PEIPNet) for efficient and effective image-inpainting. Unlike other state-of-the-art methods, the proposed model has a one-stage inpainting framework in which depthwise and pointwise convolutions are adopted to reduce the number of parameters and computational cost. To generate semantically appealing results, we selected three unique components: spatially-adaptive denormalization (SPADE), dense dilated convolution module (DDCM), and efficient self-attention (ESA). SPADE was adopted to conditionally normalize activations according to the mask in order to distinguish between damaged and undamaged regions. The DDCM was employed at every scale to overcome the gradient-vanishing obstacle and gradually fill in the pixels by capturing global information along the feature maps. The ESA was utilized to obtain clues from unmasked areas by extracting long-range information. In terms of efficiency, our model has the lowest operational memory compared with other state-of-the-art methods. Both qualitative and quantitative experiments demonstrate the generalized inpainting of our method on three public datasets: Paris StreetView, CelebA, and Places2.

Bi-frequency operation in a membrane external-cavity surface-emitting laser.

We report on the achievement of continuous wave bi-frequency operation in a membrane external-cavity surface-emitting laser (MECSEL), which is optically pumped with up to 4 W of 808 nm pump light. The presence of spatially specific loss of the intra-cavity high reflectivity mirror allows loss to be controlled on certain transverse cavity modes. The regions of spatially specific loss are defined through the removal of Bragg layers from the surface of the cavity high reflectivity mirror in the form of crosshair patterns with undamaged central regions, which are created using a laser ablation system incorporating a digital micromirror device (DMD). By aligning the laser cavity mode with the geometric centre of the loss patterns, the laser simultaneously operated on two Hermite-Gaussian spatial modes: the fundamental HG00 and the higher order HG11 mode. We demonstrate bi-frequency operation over a range of pump powers and sizes of spatial loss features, with a wavelength separation of approximately 5 nm centred at 1005 nm.

Single‐image snow removal algorithm based on generative adversarial networks

AbstractThe effect of snowfall on an image is not only the interference of snow particles but also snow streaks and masking effects (similar to haze). Snowy weather severely reduces the accuracy of computer vision systems. There is a lot of interest in how to effectively remove snow while preserving as much of the original image information as possible. Based on this, the authors propose an effective Generative Adversarial Network (GAN) snow removal algorithm for single images to solve the snow removal failure problem caused by irregular snow particles and snow streaks. Specifically, the authors improve the original GAN network as follows: A novel Transformer module, the Contextual Transformer (CoT) module, is adopted in the residual modules based generator. It effectively uses the contextual information of the snow streaks neighbourhood to restore the texture and information in the noisy image as much as possible based on the focus on snow streaks features. Also, using learnable Regionalized Normalization (RN‐L), potentially corrupted and undamaged regions are automatically detected for separate normalization, and global affine transformations are performed to enhance their fusion. In addition, a multi‐scale discriminator is used in the discriminator to make the discrimination more adequate and retain more details. Extensive experiments have shown that the authors’ GAN network snow removal algorithm outperforms various current networks on snow removal studies in terms of evaluation metrics on both synthetic and real datasets.

A Penalty Method for Coupling of Finite‐Element and Peridynamic Models

AbstractA classical continuum mechanics model no longer fulfills its basic assumptions, when the deformations are not smooth or discontinuous. Peridynamics (PD) as an integral formulation could better overcome these issues. Therefore, it is better suited to solve fracture problems such as crack initiation, its growth and formation of crack patterns. In PD the magnitudes of internal forces at a material point depend on the collective interaction of all material points within a subdomain called horizon. To take advances from the formulation, typically it is implemented in a mesh‐free form. In that case, it is easy to separate interactions between different material points. As consequence, a relatively high resolution is required to describe continuous deformation functions and, consequently computationally expensive. Therefore, the application of mesh‐free PD in undamaged regions requires an unnecessary high effort for receiving sufficient accurate results. In contrast, the finite element method (FEM) as a classical continuum mechanics‐based approach, is very efficient, if continuous stress distributions can be assumed. Consequently, a computational cost reduction can be achieved, if the PD is applied in the local damaged zone only and the remaining area is modeled and analyzed with the classical FEM. Realization of such an approach requires a sufficient accurate coupling of the PD and the FEM subdomains.A brief overview about different coupling approaches is given. Then the general approach of an Arlequin based method is presented. Here the coupling is achieved via an overlapping of PD and FEM areas. The coupling equations are developed and realized with help of the Penalty method. The Penalty method is considered as an alternative procedure to the Lagrange multiplier strategy without creating new unknowns, which essentially simplifies the coupled PD‐FEM approach. The validity and limits of the proposed technique are demonstrated through analysis, where the choice of the Penalty number is discussed as well as artificial wave oscillations, caused by the coupling area.

An experimental study on the ballistic performance of ultra-high hardness armor steel (Armox 600T) against 7.62 mm × 51 M61 AP projectile in the multi-hit condition

In this study, Armox 600T armor steel was ballistically tested against 7.62 mm × 51 M61 AP projectile. The experimental design was constructed on the basis of the worst-case scenario which is the highest possible impact velocity in the multi-hit condition. The ballistic tests revealed that Armox 600T could defeat the worst-case scenario with a thickness of 12 mm. Furthermore, the damaged and undamaged regions were inspected microstructurally in a detail manner aiming to observe the possible fractographic modes of the studied material. Finally, high resolution optical scanning efforts were also added to the experimental work whose results uncovers the possible improvement areas regarding the quantification of the results of ballistic testing.

Construction of damage-free digital twin of damaged aero-engine blades for repair volume generation in remanufacturing

Accurate repair volume generation from 3D scan data of damaged aero-engine blades is of great importance in additive or hybrid remanufacturing for restoring the blades to a like-new condition. In addition to material-missing damages, the blade's surface also deforms due to working in harsh environments, which makes it deviate from the nominal design geometry. Therefore, the Boolean operation between the nominal CAD model and the scanned point cloud of the damaged blade does not yield an accurate repair volume. This paper presents a new methodology to construct an accurate damage-free digital twin model of the defective blades that contains the deformations of the blade's undamaged regions. The Boolean difference between the scan data of the damaged blade and its damage-free digital twin yields the repair volume with a smooth geometric transition at the interface of the repair patch and unrepaired regions. At first, the data points of damaged regions of the blade surface are detected and eliminated from the scan through a region growing segmentation. Then, a CAD-to-scan non-rigid registration algorithm deforms the nominal CAD model of the blade to best match it to the scanned point cloud in the undamaged regions. The non-rigid registration algorithm iteratively minimizes the distance between two datasets under the local rigidity constraint to avoid shrinkage and expansion of the deformed CAD model. A constrained point-to-surface weighted correspondence search method is proposed to reduce the influence of noise and unreliable correspondences on the non-rigid registration. The results of numerical and experimental case studies have demonstrated that the proposed method is accurate and robust to noise, and it can be effectively applied to construct a damage-free digital twin model for repair volume generation.

Global chromatin mobility induced by a DSB is dictated by chromosomal conformation and defines the HR outcome.

Repair of DNA double-strand breaks (DSBs) is crucial for genome integrity. A conserved response to DSBs is an increase in chromatin mobility that can be local, at the site of the DSB, or global, at undamaged regions of the genome. Here, we address the function of global chromatin mobility during homologous recombination (HR) of a single, targeted, controlled DSB. We set up a system that tracks HR in vivo over time and show that two types of DSB-induced global chromatin mobility are involved in HR, depending on the position of the DSB. Close to the centromere, a DSB induces global mobility that depends solely on H2A(X) phosphorylation and accelerates repair kinetics, but is not essential. In contrast, the global mobility induced by a DSB away from the centromere becomes essential for HR repair and is triggered by homology search through a mechanism that depends on H2A(X) phosphorylation, checkpoint progression, and Rad51. Our data demonstrate that global mobility is governed by chromosomal conformation and differentially coordinates repair by HR.

Genetic characterisation of Tanqua (von Linstow, 1879) (Nematoda: Gnathostomatidae) larval forms including new host and locality records.

In an unrelated study of spotted snakehead fish Channa punctata (Bloch) of family Channidae (N = 103) from Bangladesh, ten fish had taupe and clear coloured cysts attached to the intestinal mesentery. Investigation of the cysts revealed larval nematodes. The larvae were damaged and not suitable for detailed morphological study, however, key features such as tooth like projections of the pseudolabia and lateral pseudolabium were observed in specimens with undamaged cephalic regions. Molecular characterisation was undertaken and although the parasite genetic material was poor, five of the twelve nematode larvae through sequencing of the 18S ribosomal RNA gene, showed 98.17% match with sequences assigned for Tanqua tiara (accession number JF934728) deposited in GenBank. The prevalence of infection was 9.7% and the mean intensity 2.70. Tanqua has not previously been identified in fish, or from the definitive host, the Asian water monitor Varanus salvator (Laurenti, 1768) of family Varanidae (class Reptilia), in Bangladesh. Therefore, this study represents a new host and locality record for this nematode species. In many previous reports from this region, nematode larvae have been identified morphologically and assigned to a diverse range of nematode genera. Some confusion therefore exists regarding their accuracy and further investigations are required using molecular methodology to clarify the species of larval nematodes which infect edible fish in Bangladesh.

The role of the hippocampus in statistical learning and language recovery in persons with post stroke aphasia

Although several studies have aimed for accurate predictions of language recovery in post stroke aphasia, individual language outcomes remain hard to predict. Large-scale prediction models are built using data from patients mainly in the chronic phase after stroke, although it is clinically more relevant to consider data from the acute phase. Previous research has mainly focused on deficits, i.e., behavioral deficits or specific brain damage, rather than compensatory mechanisms, i.e., intact cognitive skills or undamaged brain regions. One such unexplored brain region that might support language (re)learning in aphasia is the hippocampus, a region that has commonly been associated with an individual’s learning potential, including statistical learning. This refers to a set of mechanisms upon which we rely heavily in daily life to learn a range of regularities across cognitive domains. Against this background, thirty-three patients with aphasia (22 males and 11 females, M = 69.76 years, SD = 10.57 years) were followed for 1 year in the acute (1–2 weeks), subacute (3–6 months) and chronic phase (9–12 months) post stroke. We evaluated the unique predictive value of early structural hippocampal measures for short-term and long-term language outcomes (measured by the ANELT). In addition, we investigated whether statistical learning abilities were intact in patients with aphasia using three different tasks: an auditory-linguistic and visual task based on the computation of transitional probabilities and a visuomotor serial reaction time task. Finally, we examined the association of individuals’ statistical learning potential with acute measures of hippocampal gray and white matter. Using Bayesian statistics, we found moderate evidence for the contribution of left hippocampal gray matter in the acute phase to the prediction of long-term language outcomes, over and above information on the lesion and the initial language deficit (measured by the ScreeLing). Non-linguistic statistical learning in patients with aphasia, measured in the subacute phase, was intact at the group level compared to 23 healthy older controls (8 males and 15 females, M = 74.09 years, SD = 6.76 years). Visuomotor statistical learning correlated with acute hippocampal gray and white matter. These findings reveal that particularly left hippocampal gray matter in the acute phase is a potential marker of language recovery after stroke, possibly through its statistical learning ability.

Neurodegenerative damage reduces firing coherence in a continuous attractor model of grid cells.

Grid cells in the dorsolateral band of the medial entorhinal cortex (dMEC) display strikingly regular periodic firing patterns on a lattice of positions in two-dimensional (2D) space. This helps animals to encode relative spatial location without reference to external cues. The dMEC is damaged in the early stages of Alzheimer's disease, which affects navigation ability of a disease victim, reducing the synaptic density of neurons in the network. Within an established two-dimensional continuous attractor neural network model of grid cell activity, we introduce neural sheet damage parametrized by radius and by the strength of the synaptic output for neurons in the damaged region. The mean proportionality of the grid field flow rate in the dMEC to the velocity of the model animal is maintained, but there is a broadened distribution of flow rates in the damaged case. This flow-rate-to-velocity proportionality is essential to establish coherent grid firing fields for individual grid cells for a roaming animal. When we examine the coherence of the grid cell firing field by studying Bragg peaks of the Fourier transformed lattice firing field intensity in both damaged and undamaged regions, we find that, for a wide range of damage radius and reduced synaptic strength, for undamaged model grid cells there is an incoherent firing field structure with only a single central peak. In the radius-damage plane this is adjacent to narrow bands of striped lattices (two additional Bragg peaks), which abut an orthorhombic pattern (four additional Bragg peaks), that abuts the undamaged hexagonal region (six additional Bragg peaks). Within the damaged region, grid cells show no Bragg peaks outside the central one, which shows reduced intensity with increasing damage, and outside the damaged region the central Bragg peak strength is largely unaffected. There is a reentrant region of normal grid firing fields for very large damage area. We anticipate that the modified grid cell behavior can be observed in noninvasive functional magnetic resonance imaging (fMRI) of the dMEC.

The Role of Orientation and Temperature on the Mechanical Properties of a 20 Years Old Wind Turbine Blade GFR Composite.

This work evaluates the mechanical properties of the glass fiber reinforced polymer (GFRP) material taken from an out of service 100 KW power wind turbine blade which has been in service life of 20 years old. Investigated samples were taken from two positions of undamaged regions at 1.6 m and 5.4 m from the rotor hub, respectively. Microstructure investigation and lay-up analysis were carried out. Fiber weight fraction of the investigated samples was ranging between 0.55–0.60. Tensile and compression tests were carried out at the temperature range from −10 °C to +50 °C on specimens which were machined so as to be loaded in the blade length direction LD, transverse to the blade length TD and off axis; 45° to the blade length. Tensile elastic modulus of the investigated GFRP was determined in the three direction tested. The number of fiber fabric layers found to be decreasing along the blade length away from the root and the density of the fibers along the length is the highest (858 gm/mm2) and in the transverse direction is the lowest (83 gm/mm2). The microstructure of the GFRP composite showed good wetting for the fiber by the polymer with some features of lack of penetration at the high density fiber bundles and some production porosity in the matrix. The tensile Properties at room temperature (RT) and high temperature are almost similar with the highest properties for the samples aligned with the blade length. The compressive strength is highest at the transverse direction samples and lowest at the blade length direction and decreasing with the increase of the test temperature. The bending properties are significantly affected by the fiber orientation with the highest properties for samples aligned with the blade length and the lowest for the samples with the transverse direction.

MiR-214-3p, a novel possible therapeutic target for the pathogenesis of osteoarthritis

MiR-214-3p, a novel possible therapeutic target for the pathogenesis of osteoarthritis

Language networks in aphasia and health: A 1000 participant activation likelihood estimation meta-analysis

Aphasia recovery post-stroke is classically and most commonly hypothesised to rely on regions that were not involved in language premorbidly, through ‘neurocomputational invasion’ or engagement of ‘quiescent homologues’. Contemporary accounts have suggested, instead, that recovery might be supported by under-utilised areas of the premorbid language network, which are downregulated in health to save neural resources (‘variable neurodisplacement’). Despite the importance of understanding the neural bases of language recovery clinically and theoretically, there is no consensus as to which specific regions are more likely to be activated in post-stroke aphasia (PSA) than healthy individuals. Accordingly, we performed an Activation Likelihood Estimation (ALE) meta-analysis of language functional neuroimaging studies in PSA. We obtained coordinate-based functional neuroimaging data for 481 individuals with aphasia following left-hemisphere stroke and 530 linked controls from 33 studies that met predefined inclusion criteria. ALE identified regions of consistent, above-chance spatial convergence of activation, as well as regions of significantly different activation likelihood, between participant groups and language tasks. Overall, these findings dispute the prevailing theory that aphasia recovery involves recruitment of novel right hemisphere territory into the language network post-stroke. Instead, multiple regions throughout both hemispheres were consistently activated during language tasks in both PSA and controls. Regions of the right anterior insula, frontal operculum and inferior frontal gyrus (IFG) pars opercularis were more likely to be activated across all language tasks in PSA than controls. Similar regions were more likely to be activated during higher than lower demand comprehension or production tasks, consistent with them representing enhanced utilisation of spare capacity within right hemisphere executive-control related regions. This provides novel evidence that ‘variable neurodisplacement’ underlies language network changes that occur post-stroke. Conversely, multiple undamaged regions were less likely to be activated across all language tasks in PSA than controls, including domain-general regions of medial superior frontal and paracingulate cortex, right IFG pars triangularis and temporal pole. These changes might represent functional diaschisis, and demonstrate that there is not global, undifferentiated upregulation of all domain-general neural resources during language in PSA. Such knowledge is essential if we are to design neurobiologically-informed therapeutic interventions to facilitate language recovery.

Calculation of Thermal Fields of Cracked Concrete at Elevated Temperatures

This paper analyzes the effects of cracking on the thermal field of concrete at elevated temperatures. In four concrete specimens with pre-made cracks, fire tests were performed. Then finite element analysis and theoretical analysis were conducted, which have indicated that heat conduction was the primary source of heat transfer in cracked concrete. At last mathematical software MATLAB was used to calculate the temperatures distributions of a simplified model based on theoretical analysis, which were compared with the test results. The results show that as the thermal diffusion of air is far greater than that of concrete, there is an increase in the thermal propagation through the cracked regions in comparison with undamaged regions, and the temperatures increase with the increase of cracks widths. The temperature of concrete farther away from a crack was less affected because concrete has a lower thermal diffusion coefficient. The water content of concrete has an impact on the temperature distributions, which should be considered at the early stage of fire when determining the concrete temperature distributions.