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Communication is essential for success in today’s world, making English language learning (ELL) a crucial skill. Innovative solutions are required to tackle complex language learning issues and meet the various demands of learners. Personalized learning successfully considers students’ unique interests, strengths, and weaknesses. The study investigates the revolutionary possibilities of Gated Recurrent Neural Networks (GRNN) to improve ELL-tailored training. The GRNN-ELL model dynamically adapts to the learner’s progress using powerful sequence modelling and language processing algorithms. The training and evaluation architecture and dataset are detailed with an emphasis on optimization techniques. According to the experimental data, fluency, vocabulary diversity, contextual relevance, and engagement levels are four areas where GRNN-ELL outperforms conventional measurements. With the provision of personalized learning experiences, the promotion of intercultural communication skills, and the resolution of educational demands worldwide, the results highlight the possibility of GRNN-ELL revolutionizing ELL. The study stresses the significance of individualized training in effectively acquiring a language in today’s worldwide environment.

Folium Ginkgo extract and tetramethylpyrazine sodium chloride injection (Xingxiong injection) is a compound preparation commonly used for treating cerebral ischaemia/reperfusion injury in ischaemic stroke in China. However, its potential mechanisms on ischaemic stroke remain unknown. This study explores the potential mechanisms of Xingxiong injection in vivo or in vitro. Sprague-Dawley (SD) rats were randomly assigned to five groups: the sham (normal saline), the model (normal saline) and the Xingxiong injection groups (12.5, 25 or 50 mL/kg). The rats were subjected to 2 h of middle cerebral artery occlusion (MCAO) followed by reperfusion for 14 d. Xingxiong injection was administered via intraperitoneal (i.p.) injection immediately after ischaemia induction for 14 d. Afterwards, rats were sacrificed at 14 d induced by administration of Xingxiong injection. Xingxiong injection significantly reduces infarct volume (23%) and neurological deficit scores (93%) compared with the MCAO/R group. Additionally, Xingxiong injection inhibits the loss in mitochondrial membrane potential (43%) and reduces caspase-3 level (44%), decreases NOX (41%), protein carbonyl (29%), 4-HNE (40%) and 8-OhdG (41%) levels, inhibits the expression of inflammatory factors, such as TNF-α (26%), IL-1β (34%), IL-6 (39%), MCP-1 (36%), CD11a (41%) and ICAM-1 (43%). Moreover, Xingxiong injection can increase p-Akt/Akt (35%) and Nrf2 (47%) protein expression and inhibit NLRP3 (42%) protein expression. Xingxiong injection prevents cerebral ischaemia/reperfusion injury via activating the Akt/Nrf2 pathway and inhibiting NLRP3 inflammasome. These findings provide experimental evidence for clinical use of drugs in the treatment of ischaemic stroke.

Natural musculoskeletal systems have been widely recognized as an advanced robotic model for designing robust yet flexible microbots. However, the development of artificial musculoskeletal systems at micro-nanoscale currently remains a big challenge, since it requires precise assembly of two or more materials of distinct properties into complex 3D micro/nanostructures. In this study, we report femtosecond laser programmed artificial musculoskeletal systems for prototyping 3D microbots, using relatively stiff SU-8 as the skeleton and pH-responsive protein (bovine serum albumin, BSA) as the smart muscle. To realize the programmable integration of the two materials into a 3D configuration, a successive on-chip two-photon polymerization (TPP) strategy that enables structuring two photosensitive materials sequentially within a predesigned configuration was proposed. As a proof-of-concept, we demonstrate a pH-responsive spider microbot and a 3D smart micro-gripper that enables controllable grabbing and releasing. Our strategy provides a universal protocol for directly printing 3D microbots composed of multiple materials. Musculoskeletal systems are recognized as a model for designing robust yet flexible microbots but the development of artificial musculoskeletal systems at nanoscale currently remains challenging. Here the authors report a laser programmed artificial musculoskeletal systems for prototyping 3D microbots, using relatively stiff SU-8 as the skeleton and pH-responsive proteins as the smart muscle.

HighlightsUltralight 3D NiCo compound@MXene nanocomposites that inherited hollow polyhedral skeleton and excellent conductive network were fabricated.Excellent electromagnetic absorption performance was achieved with optimal RLmin value of − 67.22 dB and ultra-wide EAB of 6.72 GHz under the low filler loading.Electromagnetic parameters and microwave absorption property can be distinctly or slightly regulated by adjusting the filler loading and decoration of Ti3C2Tx nanoflakes.The 3D hollow hierarchical architectures tend to be designed for inhibiting stack of MXene flakes to obtain satisfactory lightweight, high-efficient and broadband absorbers. Herein, the hollow NiCo compound@MXene networks were prepared by etching the ZIF 67 template and subsequently anchoring the Ti3C2Tx nanosheets through electrostatic self-assembly. The electromagnetic parameters and microwave absorption property can be distinctly or slightly regulated by adjusting the filler loading and decoration of Ti3C2Tx nanoflakes. Based on the synergistic effects of multi-components and special well-constructed structure, NiCo layered double hydroxides@Ti3C2Tx (LDHT-9) absorber remarkably achieves unexpected effective absorption bandwidth (EAB) of 6.72 GHz with a thickness of 2.10 mm, covering the entire Ku-band. After calcination, transition metal oxide@Ti3C2Tx (TMOT-21) absorber near the percolation threshold possesses minimum reflection loss (RLmin) value of − 67.22 dB at 1.70 mm within a filler loading of only 5 wt%. This work enlightens a simple strategy for constructing MXene-based composites to achieve high-efficient microwave absorbents with lightweight and tunable EAB.

The Fowan Cliff Carvings are a key part of the Dazu Grottoes. Formed in a southern and northern stretch, the 290 individual niches at Fowan were mostly sculpted from the Late Tang to the Southern Song. Previous research by archaeologists and art historians has used typological and iconographic methods to periodize these niches and debate the themes behind particular niche sculptures. This essay employs niche inscriptions in a discussion of typical Fowan niche contents, matching lay feasting activities onto the period background behind their construction. These individual case studies grant an understanding of the overall atmosphere at Fowan through the shared inclinations or connections between niches, also reflecting specific niche sculptures via holistic analysis. This method, repeatedly examining the relationship between the niches and site from the perspective of “venue”, helps us restore a sense of situatedness when facing different eras of Fowan and to understand the choice in statue content, changes in niche content, and the design underlying niche form.

The present study was designed to investigate whether Araloside C, one of the major triterpenoid compounds isolated from Aralia elata known to be cardioprotective, can improve heart function following ischaemia/reperfusion (I/R) injury and elucidate its underlying mechanisms. We observed that Araloside C concentration‐dependently improved cardiac function and depressed oxidative stress induced by I/R. Similar protection was confirmed in isolated cardiomyocytes characterized by maintaining Ca2+ transients and cell shortening against I/R. Moreover, the potential targets of Araloside C were predicted using the DDI‐CPI server and Discovery Studio software. Molecular docking analysis revealed that Araloside C could be stably docked into the ATP/ADP‐binding domain of the heat shock protein 90 (Hsp90) protein via the formation of hydrogen bonds. The binding affinity of Hsp90 to Araloside C was detected using nanopore optical interferometry and yielded KD values of 29 μM. Araloside C also up‐regulated the expression levels of Hsp90 and improved cell viability in hypoxia/reoxygenation‐treated H9c2 cardiomyocytes, whereas the addition of 17‐AAG, a pharmacologic inhibitor of Hsp90, attenuated Araloside C‐induced cardioprotective effect. These findings reveal that Araloside C can efficiently attenuate myocardial I/R injury by reducing I/R‐induced oxidative stress and [Ca2+]i overload, which was possibly related to its binding to the Hsp90 protein.

Nanoscale surface texturing, drilling, cutting, and spatial sculpturing, which are essential for applications, including thin-film solar cells, photonic chips, antireflection, wettability, and friction drag reduction, require not only high accuracy in material processing, but also the capability of manufacturing in an atmospheric environment. Widely used focused ion beam (FIB) technology offers nanoscale precision, but is limited by the vacuum-working conditions; therefore, it is not applicable to industrial-scale samples such as ship hulls or biomaterials, e.g., cells and tissues. Here, we report an optical far-field-induced near-field breakdown (O-FIB) approach as an optical version of the conventional FIB technique, which allows direct nanowriting in air. The writing is initiated from nanoholes created by femtosecond-laser-induced multiphoton absorption, and its cutting “knife edge” is sharpened by the far-field-regulated enhancement of the optical near field. A spatial resolution of less than 20 nm (λ/40, with λ being the light wavelength) is readily achieved. O-FIB is empowered by the utilization of simple polarization control of the incident light to steer the nanogroove writing along the designed pattern. The universality of near-field enhancement and localization makes O-FIB applicable to various materials, and enables a large-area printing mode that is superior to conventional FIB processing.Nanotechnology: Better writing with lightAn optical version of Focused Ion Beam technology (FIB) allows nanoscale “writing” such as surface texturing, drilling and sculpting of materials to be performed in air, avoiding the need for a vacuum which limits the application of conventional FIB. The “Optical Far-field-Induced near-field Breakdown” (O-FIB) approach has been developed by Hong-Bo Sun of Tsinghua University and colleagues at Jilin University in China and Swinburne University of Technology in Austrilia. It works by creating nanoholes with a femtosecond laser, which is controlled by sophisticated optical effects. The process can cover larger areas than conventional FIB, and with a spatial resolution below 20 nanometres. The ability to be performed in an open atmosphere offers new possibilities for nanoscale writing. These range from working on industrial scale materials such as ship hulls, down to living tissues and cells.

Non-point source (NPS) pollution has been increasingly serious in China since the 1990s. The increases of agricultural NPS pollution in China is evaluated for the period 2000−2008 by surveying the literature on water and soil pollution from fertilizers and pesticides, and assessing the surplus nitrogen balance within provinces. The main causes for NPS pollution were excessive inputs of nitrogen fertilizer and pesticides, which were partly the result of the inadequate agricultural extension services and the rapid expansion of intensive livestock production with little of waste management. The annual application of synthetic nitrogen fertilizers and pesticides in China increased by 50.7 and 119.7%, respectively, during 1991−2008. The mitigation measures to reduce NPS pollution include: correct distortion in fertilizer prices; improve incentives for the recycling of organic manure; provide farmers with better information on the sound use of agro-chemicals; and tighten the regulations and national standards on organic waste disposal and pesticides use.

Background Nonsense-mediated mRNA decay (NMD) was originally conceived as an mRNA surveillance mechanism to prevent the production of potentially deleterious truncated proteins. Research also shows NMD is an important post-transcriptional gene regulation mechanism selectively targeting many non-aberrant mRNAs. However, how natural genetic variants affect NMD and modulate gene expression remains elusive. Results Here we elucidate NMD regulation of individual genes across human tissues through genetical genomics. Genetic variants corresponding to NMD regulation are identified based on GTEx data through unique and robust transcript expression modeling. We identify genetic variants that influence the percentage of NMD-targeted transcripts (pNMD-QTLs), as well as genetic variants regulating the decay efficiency of NMD-targeted transcripts (dNMD-QTLs). Many such variants are missed in traditional expression quantitative trait locus (eQTL) mapping. NMD-QTLs show strong tissue specificity especially in the brain. They are more likely to overlap with disease single-nucleotide polymorphisms (SNPs). Compared to eQTLs, NMD-QTLs are more likely to be located within gene bodies and exons, especially the penultimate exons from the 3′ end. Furthermore, NMD-QTLs are more likely to be found in the binding sites of miRNAs and RNA binding proteins. Conclusions We reveal the genome-wide landscape of genetic variants associated with NMD regulation across human tissues. Our analysis results indicate important roles of NMD in the brain. The preferential genomic positions of NMD-QTLs suggest key attributes for NMD regulation. Furthermore, the overlap with disease-associated SNPs and post-transcriptional regulatory elements implicates regulatory roles of NMD-QTLs in disease manifestation and their interactions with other post-transcriptional regulators.

Music classification is conducive to online music retrieval, but the current music classification model finds it difficult to accurately identify various types of music, which makes the classification effect of the current music classification model poor. In order to improve the accuracy of music classification, a music classification model based on multifeature fusion and machine learning algorithm is proposed. First, we obtain the music signal, and then extract various features from the classification of the music signal, and use machine learning algorithms to describe the type of music signal and the relationship between the features. The music classifier and deep belief network machine learning models in shallow logistic regression are established, respectively. Experiments were designed for these two models to verify the applicability of the model for music classification. By comparing the experimental results, it is found that the classification accuracy of the deep confidence network model is higher than that of the logistic regression model, but the number of iterations needed for its accuracy to converge is also higher than that of the logistic regression model. Compared with other current music classification models, this model reduces the time of constructing music classifier, speeds up the speed of music classification, and can identify various types of music with high precision. The accuracy of music classification is obviously improved, which verifies the superiority of this music classification model.