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The distribution of the permafrost in the Tibetan Plateau has dramatically changed due to climate change, expressed as increasing permafrost degradation, thawing depth deepening and disappearance of island permafrost. These changes have serious impacts on the local ecological environment and the stability of engineering infrastructures. Ground penetrating radar (GPR) is used to detect permafrost active layer depth, the upper limit of permafrost and the thawing of permafrost with the season's changes. Due to the influence of complex structure in the permafrost layer, it is difficult to effectively characterize the accurate structure within the permafrost on the radar profile. In order to get the high resolution GPR profile in the Tibetan Plateau, the reverse time migration (RTM) imaging method was applied to GPR real data. In this paper, RTM algorithm is proven to be correct through the groove's model of forward modeling data. In the Beiluhe region, the imaging result of GPR RTM profiles show that the RTM of GPR makes use of diffracted energy to properly position the reflections caused by the gravels, pebbles, cobbles and small discontinuities. It can accurately determine the depth of the active layer bottom interface in the migration section. In order to prove the accuracy of interpretation results of real data RTM section, we set up the three dielectric constant models based on the real data RTM profiles and geological information, and obtained the model data RTM profiles, which can prove the accuracy of interpretation results of three-line RTM profiles. The results of three-line RTM bears great significance for the study of complex structure and freezing and thawing process of permafrost at the Beiluhe region on the Tibetan Plateau. [ABSTRACT FROM AUTHOR]

As AI systems have obtained significant performance to be deployed widely in our daily lives and human society, people both enjoy the benefits brought by these technologies and suffer many social issues induced by these systems. To make AI systems good enough and trustworthy, plenty of researches have been done to build guidelines for trustworthy AI systems. Machine learning is one of the most important parts of AI systems, and representation learning is the fundamental technology in machine learning. How to make representation learning trustworthy in real-world application, e.g., cross domain scenarios, is very valuable and necessary for both machine learning and AI system fields. Inspired by the concepts in trustworthy AI, we proposed the first trustworthy representation learning across domains framework, which includes four concepts, i.e., robustness, privacy, fairness, and explainability, to give a comprehensive literature review on this research direction. Specifically, we first introduce the details of the proposed trustworthy framework for representation learning across domains. Second, we provide basic notions and comprehensively summarize existing methods for the trustworthy framework from four concepts. Finally, we conclude this survey with insights and discussions on future research directions. [ABSTRACT FROM AUTHOR]

Software vulnerabilities (SVs) have become a common, serious, and crucial concern due to the ubiquity of computer software. Many AI-based approaches have been proposed to solve the software vulnerability detection (SVD) problem to ensure the security and integrity of software applications (in both the development and testing phases). However, there are still two open and significant issues for SVD in terms of (i) learning automatic representations to improve the predictive performance of SVD, and (ii) tackling the scarcity of labeled vulnerability datasets that conventionally need laborious labeling effort by experts. In this paper, we propose a novel approach to tackle these two crucial issues. We first exploit the automatic representation learning with deep domain adaptation for SVD. We then propose a novel cross-domain kernel classifier leveraging the max-margin principle to significantly improve the transfer learning process of SVs from imbalanced labeled into imbalanced unlabeled projects. Our approach is the first work that leverages solid body theories of the max-margin principle, kernel methods, and bridging the gap between source and target domains for imbalanced domain adaptation (DA) applied in cross-project SVD. The experimental results on real-world software datasets show the superiority of our proposed method over state-of-the-art baselines. In short, our method obtains a higher performance on F1-measure, one of the most important measures in SVD, from 1.83% to 6.25% compared to the second highest method in the used datasets. [ABSTRACT FROM AUTHOR]

This article presents one-bit supervision, a novel setting of learning with fewer labels, for image classification. Instead of the training model using the accurate label of each sample, our setting requires the model to interact with the system by predicting the class label of each sample and learn from the answer whether the guess is correct, which provides one bit (yes or no) of information. An intriguing property of the setting is that the burden of annotation largely is alleviated in comparison to offering the accurate label. There are two keys to one-bit supervision: (i) improving the guess accuracy and (ii) making good use of the incorrect guesses. To achieve these goals, we propose a multi-stage training paradigm and incorporate negative label suppression into an off-the-shelf semi-supervised learning algorithm. Theoretical analysis shows that one-bit annotation is more efficient than full-bit annotation in most cases and gives the conditions of combining our approach with active learning. Inspired by this, we further integrate the one-bit supervision framework into the self-supervised learning algorithm, which yields an even more efficient training schedule. Different from training from scratch, when self-supervised learning is used for initialization, both hard example mining and class balance are verified to be effective in boosting the learning performance. However, these two frameworks still need full-bit labels in the initial stage. To cast off this burden, we utilize unsupervised domain adaptation to train the initial model and conduct pure one-bit annotations on the target dataset. In multiple benchmarks, the learning efficiency of the proposed approach surpasses that using full-bit, semi-supervised supervision. [ABSTRACT FROM AUTHOR]

Micro-expressions reveal underlying emotions and are widely applied in political psychology, lie detection, law enforcement and medical care. Micro-expression spotting aims to detect the temporal locations of facial expressions from video sequences and is a crucial task in micro-expression recognition. In this study, the problem of micro-expression spotting is formulated as micro-expression classification per frame. We propose an effective spotting model with sliding windows called the spatio-temporal spotting network. The method involves a sliding window detection mechanism, combines the spatial features from the local key frames and the global temporal features and performs micro-expression spotting. The experiments are conducted on the CAS(ME) 2 database and the SAMM Long Videos database, and the results demonstrate that the proposed method outperforms the state-of-the-art method by 30.58 % for the CAS(ME) 2 and 23.98 % for the SAMM Long Videos according to overall F-scores. [ABSTRACT FROM AUTHOR]

Unsupervised domain adaptation methods aim at generalizing well on unlabeled test data that may have a different (shifted) distribution from the training data. Such methods are typically developed on image data, and their application to time series data is less explored. Existing works on time series domain adaptation suffer from inconsistencies in evaluation schemes, datasets, and backbone neural network architectures. Moreover, labeled target data are often used for model selection, which violates the fundamental assumption of unsupervised domain adaptation. To address these issues, we develop a benchmarking evaluation suite (AdaTime) to systematically and fairly evaluate different domain adaptation methods on time series data. Specifically, we standardize the backbone neural network architectures and benchmarking datasets, while also exploring more realistic model selection approaches that can work with no labeled data or just a few labeled samples. Our evaluation includes adapting state-of-the-art visual domain adaptation methods to time series data as well as the recent methods specifically developed for time series data. We conduct extensive experiments to evaluate 11 state-of-the-art methods on five representative datasets spanning 50 cross-domain scenarios. Our results suggest that with careful selection of hyper-parameters, visual domain adaptation methods are competitive with methods proposed for time series domain adaptation. In addition, we find that hyper-parameters could be selected based on realistic model selection approaches. Our work unveils practical insights for applying domain adaptation methods on time series data and builds a solid foundation for future works in the field. The code is available at github.com/emadeldeen24/AdaTime. [ABSTRACT FROM AUTHOR]

Early seismic prediction in tunnels has become a necessary task to prevent construction risks. The type and performance of the seismic source are crucial factors that affect its efficiency and prediction accuracy. Among the existing main types of tunnel seismic sources, both explosive and spark sources require pre-drilling and pose safety hazards. In addition, explosive sources pose a risk of damage to tunnel structure walls. Spark sources must be used in a water medium. Artificial hammer sources have weak energy and short prediction distance. This paper proposes a portable tunnel electromagnetic impulse shock source that overcomes the deficiencies of the aforementioned seismic sources. This paper elaborates on the design and working principle of the electromagnetic impulse shock source, and analyzes the electromagnetic force exerted on the hammer body during acceleration. Through finite element simulation, this paper analyzes the multi-physical field changes of the entire electromagnetic acceleration system. Meanwhile, combining experimental testing, the design parameters and energy of the seismic source are optimized to finally design a portable electromagnetic impulse shock source. The engineering measurement data results show that the seismic source can stably generate an output energy of 1500 J, and the overall weight of the seismic source does not exceed 40 kg, with a single shot time less than 30 s and an effective prediction distance over 100 m. This work has significant practical value and superiority. [ABSTRACT FROM AUTHOR]

Generalized optical multiple-input multiple-output (GOMIMO) techniques have been recently shown to be promising for high-speed optical wireless communication (OWC) systems. In this paper, we propose a novel deep learning-aided GOMIMO (DeepGOMIMO) framework for GOMIMO systems, wherein channel state information (CSI)-free detection can be enabled by employing a specially designed deep neural network (DNN)-based MIMO detector. The CSI-free DNN detector mainly consists of two modules: one is the preprocessing module, which is designed to address both the path loss and channel crosstalk issues caused by MIMO transmission, and the other is the feedforward DNN module, which is used for joint detection of spatial and constellation information by learning the statistics of both the input signal and the additive noise. Our simulation results clearly verify that, in a typical indoor 4 × 4 MIMO-OWC system using both generalized optical spatial modulation (GOSM) and generalized optical spatial multiplexing (GOSMP) with unipolar nonzero 4-level pulse-amplitude modulation (4-PAM) modulation, the proposed CSI-free DNN detector achieves near the same bit error rate (BER) performance as the optimal joint maximum-likelihood (ML) detector, but with much-reduced computational complexity. Moreover, because the CSI-free DNN detector does not require instantaneous channel estimation to obtain accurate CSI, it enjoys the unique advantages of improved achievable data rate and reduced communication time delay in comparison to the CSI-based zero-forcing DNN (ZF-DNN) detector. [ABSTRACT FROM AUTHOR]

Eutrophication has become a great concern in recent years with the algae blooms in source water resulting in a serious threat posing to the safety of drinking water. Chlorine dioxide (ClO2) has been served as an alternative oxidant for preoxidation or disinfection during drinking water treatment process due to its high oxidation efficiency and low risk of organic by-products formation. However, the generation of inorganic by-products including chlorite (ClO2−) and chlorate (ClO3−) has become a potential problem when applied in drinking water treatment. In this study, ClO2 preoxidation-assisted coagulation/precipitation process was applied to improve the raw water quality, especially algae, turbidity, chemical oxygen demand (CODMn), and UV254, and explore the formation mechanisms of inorganic by-products. It was found that the polymeric aluminum chloride (PAC) and ClO2 have shown the best raw water treatment performance with the optimal dosage of 10 mg/L and 0.8 mg/L, respectively. Moreover, the initial pH also has exhibited a notable influence on pollutants treatment and by-products generation. Due to the adverse influence of algae and natural organic matters (NOM) and the generation of by-products, it was significant to investigate their inhibition effect on the water quality and the production of ClO2− and ClO3− in the ClO2 preoxidation-assisted coagulation/precipitation process. Moreover, it was applicable of this process to apply for the algae-containing raw water (calculated as Chl.a lower than 50 μg/L) treatment with the ClO2 dosage of less than 0.8 mg/L to achieve optimum treatment performance and minimum by-products generation. [ABSTRACT FROM AUTHOR]

The resonator of a solid-state vibratory gyro is responsible for sensing angular motion. Frequency splitting of an axisymmetric-shell resonator is a common problem caused by manufacturing defects. The defect causes a frequency difference between two working modes which consist of two nodes and two antinodes. The difference leads to the loss of gyroscopic effect, and thus the resonator cannot sense angular motion. In this paper, the resonator based on an axisymmetric multi-curved surface shell structure is investigated and an approach to eliminate frequency splits is proposed. Since axisymmetric multi-curved surface shell resonators are too complex to be modeled, this paper proposes a simplified model by focusing on a common property of the axisymmetric shell. The resonator with stochastic imperfections is made equivalent to a perfect shell with an imperfect mass point. Rayleigh's energy method is used in the theoretical analysis. Finite element modeling is used to demonstrate the effectiveness of the elimination approach. In real cases, a resonator's frequency split is eliminated by the proposed approach. In this paper, errors in the theoretical analysis are discussed and steps to be taken when the deviation between assumptions and the real situation is large are figured out. The resonator has good performance after processing. The elimination approach can be applied to any kind of solid-state vibratory gyro resonators with an axisymmetric shell structure. [ABSTRACT FROM AUTHOR]

Nanocrystalline soft magnetic alloy powders are promising microwave absorbents since they can work at diverse frequencies and are stable in harsh environments. However, when the alloy powders are in austenite phase, they are out of the screen for microwave absorbents due to their paramagnetic nature. In this work, we reported a strategy to enable strong microwave absorption in nanocrystalline austenite FeCoCr powders by deformation-thermal co-induced ferromagnetism via attritor ball milling and subsequent heat treatment. Results showed that significant austenite-to-martensite transformation in the FeCoCr powders was achieved during ball milling, along with the increase in shape anisotropy from spherical to flaky. The saturation magnetization followed parabolic kinetics during ball milling and rose from 1.43 to 109.92 emu/g after milling for 4 h, while it exhibited a rapid increase to 181.58 emu/g after subsequent heat treatment at 500 °C. A considerable increase in complex permeability and hence magnetic loss capability was obtained. With appropriate modulation of complex permittivity, the resultant absorbents showed a reflection loss of below −6 dB over 8~18 GHz at thickness of 1 mm and superior stability at 300 °C. Our strategy can broaden the material selection for microwave absorbents by involving Fe-based austenite alloys and simply recover the ferromagnetism of industrial products made without proper control of the crystalline phase. [ABSTRACT FROM AUTHOR]

The fabrication of epoxy-based nanocomposite with either Multi-Wall Carbon Nanotubes (MWCNT) or Alumina nanoparticles (ALNP) as additives were managed. To ensure a decent dispersion of additives in the epoxy resin, a magnetic stirrer and a high-energy sonicator were operated with temperature control. Different additives fractions of 0.5 wt.% and 1 wt.% were used for MWCNTs and ALNP, respectively. The nanocomposites were tested by a Universal Testing System (UTS) to determine the mechanical properties of nanocomposites before and after exposure to the Inductive Core Transformer (ICT) electron beam accelerator. The results obtained were compared with the deviation of their constituents' molecular structure acquired by Fourier Transform Infrared (FTIR) spectroscopy and Keithley 2635A electrical resistivity. The results revealed an enrichment in the mechanical properties of the epoxy matrix after the addition of additives and more performance improvement occurred after irradiation. [ABSTRACT FROM AUTHOR]

In this Letter, we present the excellent negative differential resistance (NDR) characteristics of AlN/GaN double-barrier resonant tunneling diodes (RTDs) in which the active layers are grown by molecular beam epitaxy on thick GaN-on-sapphire templates manufactured by metal-organic chemical vapor deposition. Here, indium flux is introduced as surfactant to reduce the interface roughness and improve the sharpness of heterointerface during epitaxial growth of AlN/GaN/AlN quantum well. The processed device with a top collector diameter of 1 μm size demonstrates a record peak current density of 1039 kA/cm2 while simultaneously featuring a peak-to-valley current ratio of 1.23 at room temperature, excellent achievements among all the reported GaN-based RTDs on any substrates. In addition, no degradation of device performance together with free of hysteresis is observed for the 1000 times consecutive up-to-down voltage sweeps under forward bias. These remarkable achievements are attributed to the marked improvement in heterointerface quality of AlN/GaN/AlN double-barrier quantum well by adopting indium as surfactant during epitaxial growth as clarified by transmission electron microscopy analysis, which dramatically suppresses the interface roughness scattering and elements interdiffusion, thus significantly improving the NDR signatures in current–voltage curves. The obtained results in this work illustrate that indium-surfactant added epitaxy technique turns out to be a promising approach for the modulation of vertical electron resonant tunneling in III-nitride heterostructures and realization of highly reproducible and reliable AlN/GaN double-barrier RTDs, in favor of implementation for future high-power solid-state electronics operating in terahertz spectra. [ABSTRACT FROM AUTHOR]

Introduction: Many concerns were raised about the outcome of non‐vitamin K antagonist oral anticoagulants compared with warfarin in subjects with atrial fibrillation and liver disease. However, the reported relationship between their efficacy and safety was variable. This meta‐analysis was performed to evaluate this relationship. Methods: A systematic literature search up to July 2020 was performed and six studies included 50 074 subjects with atrial fibrillation and liver disease at the baseline with 32 229 non‐vitamin K antagonist oral anticoagulant consumers and 18 920 warfarin consumers. They were reporting relationships between non‐vitamin K antagonist oral anticoagulants and warfarin in subjects with atrial fibrillation and liver disease. Odds ratio (OR) with 95% confidence intervals (CIs) was calculated to evaluate the prognostic role of the efficacy and safety of non‐vitamin K antagonist oral anticoagulants compared with warfarin in subjects with atrial fibrillation and liver disease subjects using the dichotomous method with a random or fixed‐effect model. Results: Non‐vitamin K antagonist oral anticoagulants consumption was significantly related to lower all‐cause mortality in subjects with atrial fibrillation and liver disease (OR, 0.90; 95% CI, 0.81‐0.99, P =.03); lower intracranial haemorrhage (OR, 0.67; 95% CI, 0.55‐ 0.82, P <.001) and low stroke and system embolism (OR, 0.76; 95% CI, 0.68‐0.86, P <.001) compared with warfarin consumption. However, non‐vitamin K antagonist oral anticoagulants consumption was not significantly related to lower major bleeding in subjects with atrial fibrillation and liver disease (OR, 0.73; 95% CI, 0.52‐1.02, P =.06); and gastrointestinal bleeding (OR, 0.93; 95% CI, 0.58‐1.49, P =.77) compared with warfarin consumption. Conclusions: Based on this meta‐analysis, non‐vitamin K antagonist oral anticoagulant consumption may have an independent lower risk relationship with all‐cause mortality, intracranial haemorrhage, and stroke and system embolism compared with warfarin consumption in subjects with atrial fibrillation and liver disease. This relationship forces us to recommend non‐vitamin K antagonist oral anticoagulant use in subjects with atrial fibrillation and liver disease for better outcomes and to avoid any possible complications. Further studies are required. [ABSTRACT FROM AUTHOR]

The mechanical properties of copper (Cu) nanowires (NWs) wrapped by carbon nanotube (CNT) under compression are studied by molecular dynamics simulations. By constructing a new structural model, which contains a Cu NW and a CNT that is denoted as CNT@Cu, the mechanical properties, deformation process and structural transformation are investigated in terms of stress–strain relationship, number of stacking faults (SFs) and dislocations, average bond length and atomic configurations. Results show that stress–strain exhibits two nonlinear elastic contraction stages and two intervening stages of inelastic deformation. The stress of Cu NW is almost not affected by the generation and migration activities of SFs but strongly depends on the increasing ratio of SFs due to the supporting of CNT. The inelastic plastic deformation is initiated by nucleation of partial dislocations on the {110} surface and then propagates to interior along the {111} close-packed planes. Wrapped by CNT, a unique structural transformation of compressed Cu NW is found, which is from < 100 > /{111} to < 100 > /{100} through the annihilation of {111} SFs planes and formation of {100} SFs planes along the [100] crystallographic orientations. The < 100 > /{100}-structured wire would undergo nonlinear elastic contraction until to a certain large strain, and then bend near the middle part before NW fractures eventually at a very high stain. What's more, the < 100 > /{100}-structured Cu NW possess high reversibility under unloading and an interestingly structural reverse transformation from < 100 > /{100} to < 100 > /{111} structure is observed prior to the fracture of NW at a high strain for the CNT@Cu model due the support of CNT. The ultimate compressive elastic strength of {100} (UCES-{100}) and ultimate elastic stain will decrease as the temperature increases from 10 to 500 K. The UCES of pristine (UCES-pristine) and UCSE-{100} decrease as diameter decreases. [ABSTRACT FROM AUTHOR]

A large amount of oily cuttings is produced in the drilling process when the oil-based drilling fluid is used. The oil and oil-soluble additives adsorbed on the surface of the cuttings may pollute the environment. In this paper the method of silicic acid precipitation and formation of silicic acid micromicelles is used to encapsulate oil and to remove oil from the cuttings. The authors analyze the influence of the stirring time and the solution pH on the oil removal efficiency. When the pH is 2 and the stirring time is 10 min, the oil removal rate is 96%. Research into the mechanism shows the successive formation of silicic acid sol and gel in the process of silicic acid precipitation. The structure of the silicic acid micromicelles is characterized by scanning electron microscopy (SEA). The results of differential scanning calorimetry (DSC) indicate the existence of the exothermic decomposition peak of the hydrocarbons in the range from 350°C to 500°C, which proves that the micromicelle inner phase contains oil. [ABSTRACT FROM AUTHOR]

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Due to the existence of the metal casing in production wells, it is difficult for a conventional well-logging method to achieve satisfactory results. To study the possibility of measuring the formation conductivity through casing by using a transient electromagnetic (TEM) method, characteristics of the response signals received at different source-receiver spacing are investigated. Based on the advantages of the response signals at long spacing in the separation of the direct and indirect coupled signals, the corresponding differential response signals calculated with different formation conductivities are studied further. Results show that: (1) the differential signals are three orders of magnitude smaller than that of the original response signals; (2) there is a maximum and a minimum in the differential signal; (3) with the increase of the spacing, the profile of differential signal hardly changes, but moves backward on the timeline and the amplitude decreases slowly, which is in sharp contrast to the original response signals and (4) the differential signal is proportional to the difference of corresponding formation conductivities and the maximum and minimum values in the response difference are the most sensitive. The research reveals the characteristics of TEMresponses in cased-hole and the distribution of formation conductivity information, which is predicted to provide a new perspective for the design of long-spacing through-casing in the TEMconductivity logging tool and the signal processing method. [ABSTRACT FROM AUTHOR]

Rapid detection of leakage passage in dykes has become a committed step in flood prevention work. The seismic surface wave method can be given the S-wave velocity information of the near-surface (≤ 20 m), and qualitatively evaluate the transverse position, depth range, and direction of the leakage passage. The low acquisition efficiency of the cone geophone in the conventional point measurement mode does not meet the requirements of rapid detection. A single survey line has a small coverage area and lacks comparison with neighboring survey lines, so it is not possible to obtain the direction of extension of the leakage passage. In this paper, we propose a rapid detection method of the towed array seismic surface wave for leakage passage of a dyke-dam. Forty-eight gravity geophones are arranged in three columns, 16 in each column, to form the array geometry. Surface wave imaging methods are inversion and fast imaging. The main shortcomings of inversion calculation are (1) lacking shallow information, (2) low vertical resolution, and (3) multiple solutions. To overcome the above issues, the imaging calculation of the surface wave dispersion curve is implemented using fast imaging method. The proposed array geometry is used to collect seismic data. The simulated data and measured data show that fast imaging has the following advantages: (1) It can make full use of the dispersion curve of broadband seismic data, does not lose shallow information, and has high imaging accuracy. (2) It uses the dispersion curve directly for imaging, does not lose any details of velocity changes, and has a high vertical resolution. (3) The imaging results are unique. In contrast to the inversion results, the fast imaging results clearly distinguish the location of the leakage passage and highlight the lateral variability of the leakage passage. The results of the model data and measured data demonstrate the efficiency and high resolution of the towed array seismic geometry and the fast imaging method for leakage passage detection. • The array geometries can clearly display the lateral variation of the low-velocity area. • The array geometries can indicate the direction of the leakage passage. • The fast imaging method can make full use of the dispersion curves of high frequency and low frequency. • The fast imaging method can obtain unique imaging results and avoid multiple solutions. [ABSTRACT FROM AUTHOR]

The current study aimed to investigate the effects of the thymic stromal lymphopoietin (TSLP)/TSLP receptor (TSLPR) on angiogenesis following ischemic stroke in vivo and in vitro. Furthermore, whether the phosphatidylinositol 3 kinase (PI3K)/protein kinase B (AKT) pathway mediates the effects of TSLP/TSLPR on angiogenesis was explored. A rat middle cerebral artery occlusion (MCAO) model was established, and it was demonstrated that the expression levels of TSLP and TSLPR were significantly increased in the infarct area between 12 and 72 h after MCAO, as determined by ELISA and western blot analyses. TSLP injection was revealed to upregulate vascular endothelial growth factor A (VEGFA) and angiopoietin 2 (Ang-2) expression levels in the infarct area following MCAO, as determined by western blot analysis. An in vitro MCAO model was constructed by exposing human umbilical vein endothelial cells (HUVECs) to oxygen-glucose deprivation (OGD). It was revealed that the expression levels of TSLP and TSLPR were significantly increased in HUVECs subjected to OGD. TSLP treatment was revealed to induce in vitro angiogenesis by promoting cell proliferation and migration, and increasing tube length of OGD-treated HUVECs, as determined by MTT, Transwell-migration and tube formation assays, respectively. Furthermore, it was demonstrated that the PI3K/AKT pathway was activated by TSLP treatment. However, it was revealed that PI3K inhibitor, LY294002, could attenuate the effects of TSLP on in vitro angiogenesis of OGD-treated HUVECs. In conclusion, to the best of our knowledge, this study demonstrated for the first time that TSLP/TSLPR promote angiogenesis following ischemic stroke in vivo and in vitro. Furthermore, it was demonstrated that the effects of TSLP/TSLPR on angiogenesis were, at least partially, mediated via activation of the PI3K/AKT pathway. TSLP/TSLPR may serve as a potential therapeutic target for ischemic stroke treatment. [ABSTRACT FROM AUTHOR]