A 1-bit reconfigurable intelligent metasurface-based antenna for 5G application is proposed. The proposed antenna based on artificial electromagnetic metamaterial has the advantages of easy processing and low cost. This meets the requirements of future communication network development. This antenna shows that the unit cell has a stable 180° phase difference between the ON and OFF states by loading a PIN diode at 6.425–7.125 GHz. A 10 × 10 array antenna is constructed by using 2 × 2 meta-atoms to reduce the complexity of the control network. This proposed antenna can achieve ±40° beam scanning with a gain tolerance of 3 dB and a maximum gain of 18.7 dBi. In addition, beamforming performance, such as multi-beams, is also achieved. These properties ensure that the proposed antenna has great potential in wireless communication systems and microwave imaging systems.

Raman spectroscopic analysis was performed on columbite-(Mn) samples from a variety of previously studied rare-element pegmatites in Xinjiang, China, including the Jing'erquan No. 1 spodumene-subtype, Dakalasu No. 1 beryl–columbite-subtype and Kalu'an spodumene-subtype pegmatites, to quantify the relationship between the degree of metamictisation of columbite and Raman spectra. For all of the analysed columbites-(Mn), the position (p) and the full width at half maximum (FWHM) of the strongest band, A1g vibration mode related to the Nb/Ta–O bond, in the Raman spectra have a negative correlation. Combined with previously determined U–Pb isotopic data and major–minor-element data for the columbites-(Mn), the degree of metamictisation was quantified using the alpha-decay dose (D) and displacement per atom (dpa), both of which were corrected for effects caused by annealing. The results demonstrate that the columbite-(Mn) from Jing'erquan and Kalu'an are very crystalline, whereas those from Dakalasu are transitional between crystalline and amorphous stages. The main factor influencing the key parameters, i.e. band position and FWHM, of the strongest Raman band of columbite-(Mn) is metamictisation caused by radiation damage, whereas composition and crystal orientation have limited influence. A set of equations are established to quantify the degree of metamictisation of columbite using the band position and the full width at half maximum: FWHM = 8.309 × ln(aD) + 30.11 (R2 = 0.9861); p = –5.187 × ln(aD) + 867.09 (R2 = 0.966); FWHM = 8.1453 × ln(adpa) + 48.425 (R2 = 0.9822); and p = –5.078 × ln(adpa) + 855.67 (R2 = 0.9594).

A single-shot measurement of electron emittance was experimentally accomplished using a focused transfer line with a dipole. The betatron phase of electrons based on laser wakefield acceleration (LWFA) is energy dependent owing to the coupling of the longitudinal acceleration field and the transverse focusing (defocusing) field in the bubble. The phase space presents slice information after phase compensation relative to the center energy. Fitting the transverse size of the electron beam at different energy slices in the energy spectrum measured 0.27 mm mrad in the experiment. The diagnosis of slice emittance facilitates local electron quality manipulation, which is important for the development of LWFA-based free electron lasers. The quasi-3D particle-in-cell simulations matched the experimental results and analysis well.

We report here the first hundred-watt continuous wave fiber gas laser in H2-filled hollow-core photonic crystal fiber (PCF) by stimulated Raman scattering. The pump source is a homemade narrow-linewidth fiber oscillator with a 3 dB linewidth of 0.15 nm at the maximum output power of 380 W. To efficiently and stably couple several-hundred-watt pump power into the hollow core and seal the gas, a hollow-core fiber end-cap is fabricated and used at the input end. A maximum power of 110 W at 1153 nm is obtained in a 5 m long hollow-core PCF filled with 36 bar H2, and the conversion efficiency of the first Stokes power is around 48.9%. This work paves the way for high-power fiber gas Raman lasers.

In recent years, the extraction of overlapping relations has received great attention in the field of natural language processing (NLP). However, most existing approaches treat relational triples in sentences as isolated, without considering the rich semantic correlations implied in the relational hierarchy. Extracting these overlapping relational triples is challenging, given the overlapping types are various and relatively complex. In addition, these approaches do not highlight the semantic information in the sentence from coarse-grained to fine-grained. In this paper, we propose an end-to-end neural framework based on a decomposition model that incorporates multi-granularity relational features for the extraction of overlapping triples. Our approach employs an attention mechanism that combines relational hierarchy information with multiple granularities and pretrained textual representations, where the relational hierarchies are constructed manually or obtained by unsupervised clustering. We found that the different hierarchy construction strategies have little effect on the final extraction results. Experimental results on two public datasets, NYT and WebNLG, show that our mode substantially outperforms the baseline system in extracting overlapping relational triples, especially for long-tailed relations.

Water pollution by hexavalent chromium (Cr(VI)) is widespread and problematic. As a result, more research into economic Cr(VI) removal is needed. In this study, we created and employed an adsorption–reduction mechanism to remove Cr(VI). Magnetically reduced graphene oxide bentonite (MrGO-BT) is acid resistant and can undergo magnetic separation. The hydroxyl group of chitosan (CS) condensed with the functional groups on the surface of bentonite (BT), and the MrGO-BT sandwich has been fabricated and constructed from an Fe3O4 core layer sandwiched by reduced graphene oxide (rGO) and a BT shell, with CS acting as a crosslinker. Cr(VI) elimination by MrGO-BT was exothermic and spontaneous according to thermodynamic analyses. The adsorption kinetics and adsorption isotherms were characterized by the pseudo-second order kinetic theory and the Langmuir model, respectively. Regarding the elimination of Cr(VI), the greatest adsorption ability for Cr(VI) elimination achieved was 91.5 mg g–1. Fourier-transform infrared spectroscopy and X-ray photoelectron spectroscopy suggested that Cr(VI) was reduced by C–O–H on MrGO-BT to produce Cr(III) and H–C=O, and that Cr(III) chelated with amino groups or exchanged with BT after intercalation. In addition, the introduction of Cu2+ increased the positive charge of MrGO-BT and amplified the electrostatic interaction between Cr2O72− and HCrO4–, which is what caused Cr(VI) to be eliminated. Cu2+ and reduced Cr(III) combined with -NH2 on the surface of MrGO-BT to form -NH-Cr(III) or -NH-Cu2+, and Cr(VI) elimination via chelation and ion exchange was confirmed. MrGO-BT is shown to be an adsorbent with high acid resistance and good magnetic responsiveness and stability.

The Palaeo-Mesozoic geodynamic evolution of the Tangjia–Sumdo accretionary complex belt, which separates the North and South Lhasa Terrane, remains controversial. Moreover, the lack of geological records restricts the understanding of the evolution of the Sumdo Palaeo-Tethys Ocean from the middle Permian until the middle Triassic. Here we present zircon U–Pb geochronology, whole-rock geochemistry and Sr–Nd–Hf isotopic compositions of the Yeqing gabbro. Zircon U–Pb geochronology yields ages from 254 ± 1 to 249 ± 1 Ma. In situ Hf isotopic analyses yield ϵ Hf(t) values of −0.2 to +6.3. These samples have high TiO2 (3.69 wt %) and P2O5 (0.78 wt %) contents, with typical patterns like ocean island basalt (OIB). Besides, they are classified as high-Nb basalts (HNBs) based on the high content of Nb (45.3–113.5 ppm). Whole-rock Sr–Nd isotopic compositions are similar to OIB, with initial 87Sr/86Sr of 0.7047–0.7054, 143Nd/144Nd of 0.512526–0.512647 and ϵ Nd(t) of 0.3–2.7. These signatures suggest that the Yeqing gabbro is mainly derived from low-degree melting of the garnet lherzolite mantle. Based on field observations of HNBs intruding into the continental margin and their geochemical characteristics, we infer that the Yeqing gabbro was generated in a subduction environment. Combined with the regional geology of the subduction environment and the evolution of oceanic islands in the Sumdo Palaeo-Tethys Ocean, we propose that the Yeqing gabbro may represent a product of the asthenosphere upwelling through a slab window produced by subduction of seismic ridge in the Sumdo Palaeo-Tethys Ocean, called plume – subduction-zone interaction, during the late Permian to early Triassic.

The spatial structure and time evolution of tornado-like vortices in a three-dimensional cavity are studied by topological analysis and numerical simulation. The topology theory of the unsteady vortex in the rectangular coordinate system (Zhang, Zhang & Shu, J. Fluid Mech., vol. 639, 2009, pp. 343–372) is generalized to the curvilinear coordinate system. Two functions $\lambda (q_1,t)$ and $q(q_1,t)$ are obtained to determine the topology structure of the sectional streamline pattern in the cross-section perpendicular to the vortex axis and the meridional plane, respectively. The spiral direction of the sectional streamlines in the cross-section perpendicular to the vortex axis depends on the sign of $\lambda (q_1,t)$. The types of critical points in the meridional plane depend on the sign of $q(q_1,t)$. The relation between the critical points of the streamline pattern in the meridional plane and that in the cross-section perpendicular to the vortex axis is set up. The flow in a three-dimensional rectangular cavity is numerically simulated by solving the three-dimensional Navier–Stokes equations using high-order numerical methods. The spatial structures and the time evolutions of the tornado-like vortices in the cavity are analysed with our topology theory. Both the bubble type and spiral type of vortex breakdown are observed. They have a close relationship with the vortex structure in the cross-section perpendicular to the vortex axis. The bubble-type breakdown has a conical core and the core is non-axisymmetric in the sense of topology. A criterion for the bubble type and the spiral type based on the spatial structure characteristic of the two breakdown types is provided.

This paper develops the estimation method of mean and covariance functions of functional data with additional covariate information. With the strength of both local linear smoothing modeling and general weighing scheme, we are able to explicitly characterize the mean and covariance functions with incorporating covariate for irregularly spaced and sparsely observed longitudinal data, as typically encountered in engineering technology or biomedical studies, as well as for functional data which are densely measured. Theoretically, we establish the uniform convergence rates of the estimators in the general weighing scheme. Monte Carlo simulation is conducted to investigate the finite-sample performance of the proposed approach. Two applications including the children growth data and white matter tract dataset obtained from Alzheimer's Disease Neuroimaging Initiative study are also provided.

Instrument delivery is critical part in vascular intervention surgery. Due to the soft-body structure of instruments, the relationship between manipulation commands and instrument motion is non-linear, making instrument delivery challenging and time-consuming. Reinforcement learning has the potential to learn manipulation skills and automate instrument delivery with enhanced success rates and reduced workload of physicians. However, due to the sample inefficiency when using high-dimensional images, existing reinforcement learning algorithms are limited on realistic vascular robotic systems. To alleviate this problem, this paper proposes discrete soft actor-critic with auto-encoder (DSAC-AE) that augments SAC-discrete with an auxiliary reconstruction task. The algorithm is applied with distributed sample collection and parameter update in a robot-assisted preclinical environment. Experimental results indicate that guidewire delivery can be automatically implemented after 50k sampling steps in less than 15 h, demonstrating the proposed algorithm has the great potential to learn manipulation skill for vascular robotic systems.

The identification of herbicide tolerance is essential for effective chemical weed control. According to whole-plant dose–response assays, none of 29 pond lovegrass [Eragrostis japonica (Thunb.) Trin.] populations were sensitive to penoxsulam. The effective dose values of penoxsulam causing 50% inhibition of fresh weight (GR50: 105.14 to 148.78 g ai ha−1) in E. japonica populations were much higher than the label rate of penoxsulam (15 to 30 g ai ha−1) in the field. This confirmed that E. japonica was tolerant to penoxsulam. Eragrostis japonica populations showed 52.83- to 74.76-fold higher tolerance to penoxsulam than susceptible barnyardgrass [Echinochloa crus-galli (L.) P. Beauv.]. The mechanisms of tolerance to penoxsulam in E. japonica were also identified. In vitro activity assays revealed that the penoxsulam concentration required to inhibit 50% of the acetolactate synthase (ALS) activity (IC50) was 12.27-fold higher in E. japonica than in E. crus-galli. However, differences in the ALS gene, previously found to endow target-site resistance in weeds, were not detected in the sequences obtained. Additionally, the expression level of genes encoding ALS in E. japonica was approximately 2-fold higher than in E. crus-galli after penoxsulam treatment. Furthermore, penoxsulam tolerance can be significantly reversed by three cytochrome P450 monooxygenase (CytP450) inhibitors (1-aminobenzotriazole, piperonyl butoxide, and malathion), and the activity of NADPH-dependent cytochrome P450 reductase toward penoxsulam in E. japonica increased significantly (approximately 7-fold higher) compared with that of treated E. crus-galli. Taken together, these results indicate that lower ALS sensitivity, relatively higher ALS expression levels, and stronger metabolism of CytP450s combined to bring about penoxsulam tolerance in E. japonica.

The increasing FDI in Africa from China and India in recent years has drawn the attention of scholars, policy makers, and the media. Africa is an arena where the two emerging giants compete on different bases. Indian firms have the advantage of institutional proximity and large diaspora communities in Africa, while Chinese firms rely on government-to-government relationship-building. The rivalry between India's soft power and Chinese hard power in Africa will continue for the foreseeable future.

Metonymy resolution (MR) is a challenging task in the field of natural language processing. The task of MR aims to identify the metonymic usage of a word that employs an entity name to refer to another target entity. Recent BERT-based methods yield state-of-the-art performances. However, they neither make full use of the entity information nor explicitly consider syntactic structure. In contrast, in this paper, we argue that the metonymic process should be completed in a collaborative manner, relying on both lexical semantics and syntactic structure (syntax). This paper proposes a novel approach to enhancing BERT-based MR models with hard and soft syntactic constraints by using different types of convolutional neural networks to model dependency parse trees. Experimental results on benchmark datasets (e.g., ReLocaR, SemEval 2007 and WiMCor) confirm that leveraging syntactic information into fine pre-trained language models benefits MR tasks.

Maternal gestational weight gain (GWG) is an important determinant of infant birth weight, and having adequate total GWG has been widely recommended. However, the association of timing of GWG with birth weight remains controversial. We aimed to evaluate this association, especially among women with adequate total GWG. In a prospective cohort study, pregnant women’s weight was routinely measured during pregnancy, and their GWG was calculated for the ten intervals: the first 13, 14–18, 19–23, 24–28, 29–30, 31–32, 33–34, 35–36, 37–38 and 39–40 weeks. Birth weight was measured, and small-for-gestational-age (SGA) and large-for-gestational-age were assessed. Generalized linear and Poisson models were used to evaluate the associations of GWG with birth weight and its outcomes after multivariate adjustment, respectively. Of the 5049 women, increased GWG in the first 30 weeks was associated with increased birth weight for male infants, and increased GWG in the first 28 weeks was associated with increased birth weight for females. Among 1713 women with adequate total GWG, increased GWG percent between 14 and 23 weeks was associated with increased birth weight. Moreover, inadequate GWG between 14 and 23 weeks, compared with the adequate GWG, was associated with an increased risk of SGA (43 (13·7 %) v. 42 (7·2 %); relative risk 1·83, 95 % CI 1·21, 2·76). Timing of GWG may influence infant birth weight differentially, and women with inadequate GWG between 14 and 23 weeks may be at higher risk of delivering SGA infants, despite having adequate total GWG.