Pulsed laser deposition of a Ga2O3 thin film for an optoelectronic synaptic device.

With the rapid development of information era, the traditional von Neumann architecture faces the computing bottleneck, and integration of memory and perception is regarded as a potential solution. Herein, a Ga2O3/Si heterojunction based multi-modulated optoelectronic synaptic device is fabricated and demonstrated. As stimulated by ultraviolet (UV) optical spikes, the heterojunction device reveals typical synaptic functions of excitatory-postsynaptic current (EPSC), paired-pulse facilitation (PPF), spike-timing-dependent plasticity (STDP), and switch between short-term memory (STM) and long-term memory (LTM). In addition, stronger stimulations like higher reading voltage, stronger optical stimulated intensity, and longer pulse duration time can significantly prolong the attenuation of EPSC, which contributes to the improvement of the forgetting process. Our work provides a potential strategy for future neuromorphic computation through a UV light driven stimulation.

UGDAS: Unsupervised graph-network based denoiser for abstractive summarization in biomedical domain.

Abstractive summarization models can generate summary auto-regressively, but the quality is often impacted by the noise in the text. Learning cross-sentence relations is a crucial step in this task and the graph-based network is more effective to capture the sentence relationship. Moreover, knowledge is very important to distinguish the noise of the text in special domain. A novel model structure called UGDAS is proposed in this paper, which combines a sentence-level denoiser based on an unsupervised graph-network and an auto-regressive generator. It utilizes domain knowledge and sentence position information to denoise the original text and further improve the quality of generated summaries. We use the recently-introduced dataset CORD-19 (COVID-19 Open Research Dataset) on text summarization task, which contains large-scale data on coronaviruses. The experimental results show that our model achieves the SOTA (state-of-the-art) result on CORD-19 dataset and outperforms the related baseline models on the PubMed Abstract dataset.

Enhancement of Mass and Charge Transfer during Carbon Dioxide Photoreduction by Enhanced Surface Hydrophobicity without a Barrier Layer.

The CO2 reduction reaction (CRR) represents a promising route for the clean utilization of renewable resources. But mass-transfer limitations seriously hinder the forward step. Enhancing the surface hydrophobicity by using polymers has been proved to be one of the most efficient strategies. However, as macromolecular organics, polymers on the surface hinder the transfer of charge carriers from catalysts to reactants. Herein, we describe an in-situ surface fluorination strategy to enhance the surface hydrophobicity of TiO2 without a barrier layer of organics, thus facilitating the mass transfer of CO2 to catalysts and charge transfer. With less obstruction to charge transfer, a higher CO2, and lower H+ surface concentration, the photocatalytic CRR generation rate of methanol (CH3 OH) is greatly enhanced to up to 247.15 µmol g-1 h-1 . Furthermore, we investigated the overall defects; enhancing the surface hydrophobicity of catalysts provides a general and reliable method to improve the competitiveness of CRR.

Modulation on the Iron Centers by Selective Synthesis of Organic Ligands with Stereo-Specific Conformations.

Advanced fabrication of surface metal-organic complexes with specific coordination configuration and metal centers will facilitate to exploit novel nanomaterials with attractive electronic/magnetic properties. The precise on-surface synthesis provides an appealing strategy for in situ construction of complex organic ligands from simple precursors autonomously. In this paper, distinct organic ligands with stereo-specific conformation are separately synthesized through the well-known dehalogenative coupling. More interestingly, the exo-bent ligands promote the mono-iron chelated complexes with the Fe center significantly decoupled from the surface and of high spin, while the endo-bent ligands lead to bi-iron chelated ones instead with ferromagnetic properties.

Deep scaled dot-product attention based domain adaptation model for biomedical question answering.

Biomedical text mining is becoming increasingly important as the number of biomedical documents grow rapidly. Deep learning has boosted the development of biomedical text mining models. However, as deep learning models require a large amount of training data, a hierarchical attention based transfer learning model is proposed in this paper for the question answering task in biomedical field which lacks of sufficient training data. We adopt BERT (Bidirectional Encoder Representation Transformers), which has the ability to learn from large-scale unsupervised data, to enrich the semantic representation in our model. Especially, the scaled dot-product attention mechanism captures the question interaction clues for passage encoding. The domain adaptation technique of fine-tuning is used to reinforce the performance, which penalizes the deviations from the source model's parameters and remembers the knowledge of source domain. We evaluate the system performance on the open data set of BioASQ-Task B. The results show that our system achieves the state-of-the-art performance without any handcrafted features and outperforms the best solution for factoid questions in 2016 and 2017 BioASQ-Task B.

Ultrahigh conductivity in Weyl semimetal NbAs nanobelts.

In two-dimensional (2D) systems, high mobility is typically achieved in low-carrier-density semiconductors and semimetals. Here, we discover that the nanobelts of Weyl semimetal NbAs maintain a high mobility even in the presence of a high sheet carrier density. We develop a growth scheme to synthesize single crystalline NbAs nanobelts with tunable Fermi levels. Owing to a large surface-to-bulk ratio, we argue that a 2D surface state gives rise to the high sheet carrier density, even though the bulk Fermi level is located near the Weyl nodes. A surface sheet conductance up to 5-100 S per □ is realized, exceeding that of conventional 2D electron gases, quasi-2D metal films, and topological insulator surface states. Corroborated by theory, we attribute the origin of the ultrahigh conductance to the disorder-tolerant Fermi arcs. The evidenced low-dissipation property of Fermi arcs has implications for both fundamental study and potential electronic applications.

Pressure-induced superconductivity in a three-dimensional topological material ZrTe5.

As a new type of topological materials, ZrTe5 shows many exotic properties under extreme conditions. Using resistance and ac magnetic susceptibility measurements under high pressure, while the resistance anomaly near 128 K is completely suppressed at 6.2 GPa, a fully superconducting transition emerges. The superconducting transition temperature Tc increases with applied pressure, and reaches a maximum of 4.0 K at 14.6 GPa, followed by a slight drop but remaining almost constant value up to 68.5 GPa. At pressures above 21.2 GPa, a second superconducting phase with the maximum Tc of about 6.0 K appears and coexists with the original one to the maximum pressure studied in this work. In situ high-pressure synchrotron X-ray diffraction and Raman spectroscopy combined with theoretical calculations indicate the observed two-stage superconducting behavior is correlated to the structural phase transition from ambient Cmcm phase to high-pressure C2/m phase around 6 GPa, and to a mixture of two high-pressure phases of C2/m and P-1 above 20 GPa. The combination of structure, transport measurement, and theoretical calculations enable a complete understanding of the emerging exotic properties in 3D topological materials under extreme environments.

Biomedical semantic indexing by deep neural network with multi-task learning.

BACKGROUND: Biomedical semantic indexing is important for information retrieval and many other research fields in bioinformatics. It annotates biomedical citations with Medical Subject Headings. In face of unbalanced category distribution in the training data, sampling methods are difficult to apply for semantic indexing task. RESULTS: In this paper, we present a novel deep serial multi-task learning model. The primary task treats the biomedical semantic indexing as a multi-label text classification issue that considers the relations of the labels. The auxiliary task is a regression task that predicts the MeSH number of the citation and provides hints for the network to make it converge faster. The experimental results on the BioASQ-Task5A open dataset show that our model outperforms the state-of-the-art solution "MTI", proposed by the US National Library of Medicine. Further, it not only achieves the highest precision among all the solutions in BioASQ-Task5A but also has faster convergence speed compared with some naive deep learning methods. CONCLUSIONS: Rather than parallel in an ordinary multi-task structure, the tasks in our model are serial and tightly coupled. It can achieve satisfied performance without any handcrafted feature.

Prediction of Intrinsic Ferromagnetic Ferroelectricity in a Transition-Metal Halide Monolayer.

The realization of multiferroics in nanostructures, combined with a large electric dipole and ferromagnetic ordering, could lead to new applications, such as high-density multistate data storage. Although multiferroics have been broadly studied for decades, ferromagnetic ferroelectricity is rarely explored, especially in two-dimensional (2D) systems. Here we report the discovery of 2D ferromagnetic ferroelectricity in layered transition-metal halide systems. On the basis of first-principles calculations, we reveal that a charged CrBr_{3} monolayer exhibits in-plane multiferroicity, which is ensured by the combination of orbital and charge ordering as realized by the asymmetric Jahn-Teller distortions of octahedral Cr─Br_{6} units. As an example, we further show that (CrBr_{3})_{2}Li is a ferromagnetic ferroelectric multiferroic. The explored phenomena and mechanism of multiferroics in this 2D system not only are useful for fundamental research in multiferroics but also enable a wide range of applications in nanodevices.

Pressure-Induced New Topological Weyl Semimetal Phase in TaAs.

We report a new pressure-induced phase in TaAs with different Weyl fermions than the ambient structure with the aid of theoretical calculations, experimental transport and synchrotron structure investigations up to 53 GPa. We show that TaAs transforms from an ambient I4_{1}md phase (t-TaAs) to a high-pressure hexagonal P-6m2 (h-TaAs) phase at 14 GPa, along with changes of the electronic state from containing 24 Weyl nodes distributed at two energy levels to possessing 12 Weyl nodes at an isoenergy level, which substantially reduces the interference between the surface and bulk states. The new pressure-induced phase can be reserved upon releasing pressure to ambient condition, which allows one to study the exotic behavior of a single set of Weyl fermions, such as the interplay between surface states and other properties.

[Influence of cefuroxime sodium on synaptic plasticity of parallel fiber-Purkinje cells in young rats].

OBJECTIVE: To investigate the influence of cefuroxime sodium (CS) on the electrophysiological function of cerebellar Purkinje cells (PCs) in Sprague-Dawley rats. METHODS: Postnatal day 7 (P7) Sprague-Dawley rats were divided into early administration I and II groups (administered from P7 to P14) and late administration group (administered from P14 to P21), and all the groups received intraperitoneally injected CS. The control groups for early and late administration groups were also established and treated with intraperitoneally injected normal saline of the same volume. There were 10 rats in each group. The rats in the early administration I group and early administration control group were sacrificed on P15, and those in the early administration II group, late administration group, and late administration control group were sacrificed on P22. The whole-cell patch-clamp technique was used to record inward current and action potential of PCs on cerebellar slices, as well as the long-term depression (LTD) of excitatory postsynaptic current (EPSC) in PCs induced by low-frequency stimulation of parallel fiber (PF). RESULTS: Compared with the control groups, the early and late administration groups had a slightly higher magnitude of inward current and a slightly higher amplitude of action potential of PCs (P>0.05). All administration groups had a significantly higher degree of EPSC inhibition than the control groups (P<0.01), and the early administration II group had a significantly greater degree of EPSC inhibition than the late administration group (P<0.01). CONCLUSIONS: Early CS exposure after birth affects the synaptic plasticity of PF-PCs in the cerebellum of young rats, which persists after drug withdrawal.

[Protective effect of succinic acid on cerebellar Purkinje cells of neonatal rats with convulsion].

OBJECTIVE: To investigate the protective effect of succinic acid (SA) on the cerebellar Purkinje cells (PCs) of neonatal rats with convulsion. METHODS: A total of 120 healthy neonatal Sprague-Dawley rats aged 7 days were randomly divided into a neonatal period group and a developmental period group. Each of the two groups were further divided into 6 sub-groups: normal control, convulsion model, low-dose phenobarbital (PB) (30 mg/kg), high-dose PB (120 mg/kg), low-dose SA (30 mg/kg), and high-dose SA (120 mg/kg). Intraperitoneal injection of pentylenetetrazole was performed to establish the convulsion model. The normal control group was treated with normal saline instead. The rats in the neonatal group were sacrificed at 30 minutes after the injection of PB, SA, or normal saline, and the cerebellum was obtained. Those in the developmental group were sacrificed 30 days after the injection of PB, SA, or normal saline, and the cerebellum was obtained. Whole cell patch clamp technique was used to record the action potential (AP) of PCs in the cerebellar slices of neonatal rats; the parallel fibers (PF) were stimulated at a low frequency to induce excitatory postsynaptic current (EPSC). The effect of SA on long-term depression (LTD) of PCs was observed. RESULTS: Compared with the normal control groups, the neonatal and developmental rats with convulsion had a significantly higher AP frequency of PCs (P<0.05), and the developmental rats with convulsion had a significantly decreased threshold stimulus (P<0.01) and a significantly greater inhibition of the amplitude of EPSC in PCs (P<0.05). Compared with the normal control groups, the neonatal and developmental rats with convulsion in the high-dose PB groups had a significantly decreased threshold stimulus (P<0.01), a significantly higher AP frequency of PCs (P<0.05), and a significantly greater inhibition of EPSC in PCs (P<0.05). Compared with the neonatal and developmental rats in the convulsion model groups, those in the high-dose SA groups had a significantly decreased AP frequency of PCs (P<0.05). The developmental rats in the low- and high-dose SA groups had a significantly higher AP threshold than those in the convulsion model group (P<0.05). CONCLUSIONS: The high excitability of PCs and the abnormal PF-PC synaptic plasticity caused by convulsion in neonatal rats may last to the developmental period, which can be aggravated by PB, while SA can reduce the excitability of PCs in neonatal rats with convulsion and repair the short- and long-term abnormalities of LTD of PCs caused by convulsion.

Foreground Capture Feature Pyramid Network-Oriented Object Detection in Complex Backgrounds.

Feature pyramids are widely adopted in visual detection models for capturing multiscale features of objects. However, the utilization of feature pyramids in practical object detection tasks is prone to complex background interference, resulting in suboptimal capture of discriminative multiscale foreground semantic features. In this article, a foreground capture feature pyramid network (FCFPN) for multiscale object detection is proposed, to address the problem of inadequate feature learning in complex backgrounds. FCFPN consists of a foreground dual attention (FDA) module and a pathway aggregation (PA) structure. Specifically, the FDA mechanism activates top-down foreground channel responses and lateral spatial foreground location features, so that channel and spatial foreground features are adequately captured. Then, the PA module adaptively learns the fusion weights of multiscale features at different levels of the feature pyramid, which enhances the complementarity of semantic information between different levels of the foreground feature maps. Since the fusion weights are learned adaptively based on different pyramid levels, the detection model accordingly retains the gained information of feature sizes and suppresses the conflicting information. The evaluations on public datasets and the self-built complex background dataset demonstrate that the detection average precision (AP) and the feature learning performance of the proposed method are superior compared with other FPNs, which proves the effectiveness of the proposed FCFPN.

Solar-driven CO2-to-ethanol conversion enabled by continuous CO2 transport via a superhydrophobic Cu2O nano fence.

The overall photocatalytic CO2 reduction reaction presents an eco-friendly approach for generating high-value products, specifically ethanol. However, ethanol production still faces efficiency issues (typically formation rates <605 µmol g-1 h-1). One significant challenge arises from the difficulty of continuously transporting CO2 to the catalyst surface, leading to inadequate gas reactant concentration at reactive sites. Here, we develop a mesoporous superhydrophobic Cu2O hollow structure (O-CHS) for efficient gas transport. O-CHS is designed to float on an aqueous solution and act as a nano fence, effectively impeding water infiltration into its inner space and enabling CO2 accumulation within. As CO2 is consumed at reactive sites, O-CHS serves as a gas transport channel and diffuser, continuously and promptly conveying CO2 from the gas phase to the reactive sites. This ensures a stable high CO2 concentration at reactive sites. Consequently, O-CHS achieves the highest recorded ethanol formation rate (996.18 µmol g-1 h-1) to the best of our knowledge. This strategy combines surface engineering with geometric modulation, providing a promising pathway for multi-carbon production.

Spatial oblivion channel attention targeting intra-class diversity feature learning.

Convolutional neural networks (CNNs) have successfully driven many visual recognition tasks including image classification. However, when dealing with classification tasks with intra-class sample style diversity, the network tends to be disturbed by more diverse features, resulting in limited feature learning. In this article, a spatial oblivion channel attention (SOCA) for intra-class diversity feature learning is proposed. Specifically, SOCA performs spatial structure oblivion in a progressive regularization for each channel after convolution, so that the network is not restricted to a limited feature learning, and pays attention to more regionally detailed features. Further, SOCA reassigns channel weights in the progressively oblivious feature space from top to bottom along the channel direction, to ensure the network learns more image details in an orderly manner while not falling into feature redundancy. Experiments are conducted on the standard classification dataset CIFAR-10/100 and two garbage datasets with intra-class diverse styles. SOCA improves SqueezeNet, MobileNet, BN-VGG-19, Inception and ResNet-50 in classification accuracy by 1.31%, 1.18%, 1.57%, 2.09% and 2.27% on average, respectively. The feasibility and effectiveness of intra-class diversity feature learning in SOCA-enhanced networks are verified. Besides, the class activation map shows that more local detail feature regions are activated by adding the SOCA module, which also demonstrates the interpretability of the method for intra-class diversity feature learning.

Second-order Jahn-Teller effect induced high-temperature ferroelectricity in two-dimensional NbO2X (X = I, Br).

Based on the first-principles calculations, we investigated the ferroelectric properties of two-dimensional (2D) materials NbO2X (X = I, Br). Our cleavage energy analysis shows that exfoliating one NbO2I monolayer from its existing bulk counterpart is feasible. The phonon spectrum and molecular dynamics simulations confirm the dynamic and thermal stability of the monolayer structures for both NbO2I and NbO2Br. Total energy calculations show that the ferroelectric phase is the ground state for both materials, with the calculated in-plane ferroelectric polarizations being 384.5 pC m-1 and 375.2 pC m-1 for monolayers NbO2I and NbO2Br, respectively. Moreover, the intrinsic Curie temperature TC of monolayer NbO2I (NbO2Br) is as high as 1700 K (1500 K) from Monte Carlo simulation. Furthermore, with the orbital selective external potential method, the origin of ferroelectricity in NbO2X is revealed as the second-order Jahn-Teller effect. Our findings suggest that monolayers NbO2I and NbO2Br are promising candidate materials for practical ferroelectric applications.

Improving Biomedical Question Answering by Data Augmentation and Model Weighting.

Biomedical Question Answering aims to extract an answer to the given question from a biomedical context. Due to the strong professionalism of specific domain, it's more difficult to build large-scale datasets for specific domain question answering. Existing methods are limited by the lack of training data, and the performance is not as good as in open-domain settings, especially degrading when facing to the adversarial sample. We try to resolve the above issues. First, effective data augmentation strategies are adopted to improve the model training, including slide window, summarization and round-trip translation. Second, we propose a model weighting strategy for the final answer prediction in biomedical domain, which combines the advantage of two models, open-domain model QANet and BioBERT pre-trained in biomedical domain data. Finally, we give adversarial training to reinforce the robustness of the model. The public biomedical dataset collected from PubMed provided by BioASQ challenge is used to evaluate our approach. The results show that the model performance has been improved significantly compared to the single model and other models participated in BioASQ challenge. It can learn richer semantic expression from data augmentation and adversarial samples, which is beneficial to solve more complex question answering problems in biomedical domain.

First-principles study of magnetic interactions and excitations in antiferromagnetic van der Waals material MPX3(M=Mn, Fe, Co, Ni; X=S, Se).

Transition metal phosphorus trichalcogenides MPX3(M = Mn, Fe, Co, Ni; X = S, Se), as layered van der Waals antiferromagnetic (AFM) materials, have emerged as a promising platform for exploring two-dimensional (2D) magnetism. Based on density functional theory, we present a comprehensive investigation of the electronic and magnetic properties of MPX3. We calculated the spin exchange interactions as well as magnetocrystalline anisotropy energy. The numerical results reveal thatJ3is AFM in all cases, andJ2is significantly smaller compared to bothJ3andJ1. This behavior can be understood with regard to exchange paths and electron filling. Compared to other materials within this family, FePS3and CoPS3demonstrate significant easy-axis anisotropy. Using the obtained parameters, we estimated the Néel temperatureTNand Curie-Weiss temperatureθCW, and the results are in good agreement with the experimental observations. We further calculated the magnon spectra and successfully reproduce several typical features observed experimentally. Finally, we give helpful suggestions for the strong constraints about the range of non-negligible magnetic interactions based on the relations between magnon eigenvalues at high-symmetrykpoints in honeycomb lattices.

Cannabinoid-2 receptor activation protects against infarct and ischemia-reperfusion heart injury.

Endocannabinoid system is reported to be activated during myocardial ischemia-reperfusion (IR) injury and protects against heart injury. We, therefore, observed changes in endocannabinoids levels during acute myocardial infarction (AMI) and myocardial IR injury and evaluated the role of cannabinoid-2 (CB2) receptor in infarct and IR heart injury. In contrast to 16 control patients with normal coronary artery angiogram, the endocannabinoid 2-arachidonoylglycerol level in the infarct-side coronary artery of 23 AMI patients increased significantly, with increased reactive oxygen species and tumor necrosis factor-α levels in both infarct-side coronary artery and radial artery. Then, 35 C57BL/6J mice were made into SHAM, AMI, or IR models. AMI and IR groups were treated with CB2-selective agonist HU308 ((+)-(1aH,3H,5aH)-4-[2,6-dimethoxy-4-(1,1-dimethylheptyl)phenyl]-6,6-dimethylbicyclo[3.1.1]hept-2-ene-2-carbinol), with or without CB2-selective antagonist AM630 [6-iodo-2-methyl-1-[2-(4-morpholinyl)ethyl]-1H-indol-3-yl](4-methoxyphenyl)methanone through intraperitoneal injection. Compared with the SHAM, expressions of cannabinoid CB1/CB2 receptor proteins in AMI/IR animals were upregulated; production of 2-arachidonoylglycerol and anandamide and release of reactive oxygen species and tumor necrosis factor-α also increased. HU308 significantly decreased the infarct size and the levels of reactive oxygen species and tumor necrosis factor-α in AMI/IR animals. However, these effects were blocked by AM630. In conclusion, the endocannabinoid system was activated during AMI and IR, and CB2 receptor activation produces a protective role, thus offering a novel pharmaceutical target for treating these diseases.

Pharmacoinvasive therapy for ST elevation myocardial infarction in China: a pilot study.

Most patients with acute ST-elevation myocardial infarction (STEMI) cannot receive timely primary percutaneous coronary intervention (PCI) because of lack of facilities or delays in patient transfer or catheterization team mobilization. In these patients, early routine post-thrombolysis PCI might be a reasonable, useful strategy. This study investigated feasibility and safety of early PCI after successful half-dose alteplase reperfusion in a Chinese population. Patients with STEMI received half-dose alteplase if expected time delay to PCI was ≥90 min. Patients who reached clinical criteria of successful thrombolysis reperfusion were recommended to undergo diagnostic angiography within 3-24 h after thrombolysis. Patients with residual stenosis ≥70% in the infarct-related artery underwent PCI, regardless of flow or patency status. Epicardial arterial flow was assessed using thrombolysis in myocardial infarction (TIMI) flow grade and TIMI frame count (CTFC). Myocardial perfusion was assessed using myocardial blush grade (MBG) and TIMI myocardial perfusion frame count (TMPFC). Forty-nine patients were enrolled and underwent diagnostic angiography 3-11.3 h (median 6.5 h) after thrombolysis. Forty-six patients underwent PCI. No procedure-related complications occurred, except two patients who had no reflow after PCI. Twenty-two (47.8%) patients had TIMI grade 3 flow before PCI and 33 (71.7%) after PCI. CTFC was significantly improved after PCI (48.5 ± 32.1 vs. 37.9 ± 25.6, P = 0.01). MBG and TMPFC exhibited a similar improving trend after PCI, and the best myocardial perfusion tended to be achieved 3-12 h after lysis. During the 30-day follow-up, there were two deaths. The composite end point of death, cardiogenic shock, heart failure, reinfarction, and recurrent ischemia occurred in four patients. TIMI minor bleeding occurred in four patients. No TIMI major bleeding and stroke occurred. Early routine PCI after half-dose alteplase thrombolysis in Chinese population appears feasible. A larger clinical trial should be designed to further elucidate its efficacy and safety. Early PCI after thrombolysis in STEMI: The EARLY-PCI pilot feasibility study, ChiCTR-TNC-11001363.