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Although both self-supervised single-frame and multi-frame depth estimation methods only require unlabeled monocular videos for training, the information they leverage varies because single-frame methods mainly rely on appearance-based features while multi-frame methods focus on geometric cues. Considering the complementary information of single-frame and multi-frame methods, some works attempt to leverage single-frame depth to improve multi-frame depth. However, these methods can neither exploit the difference between single-frame depth and multi-frame depth to improve multi-frame depth nor leverage multi-frame depth to optimize single-frame depth models. To fully utilize the mutual influence between single-frame and multi-frame methods, we propose a novel self-supervised training framework. Specifically, we first introduce a pixel-wise adaptive depth sampling module guided by single-frame depth to train the multi-frame model. Then, we leverage the minimum reprojection based distillation loss to transfer the knowledge from the multi-frame depth network to the single-frame network to improve single-frame depth. Finally, we regard the improved single-frame depth as a prior to further boost the performance of multi-frame depth estimation. Experimental results on the KITTI and Cityscapes datasets show that our method outperforms existing approaches in the self-supervised monocular setting., 8 pages, 2 figures, submitted to IEEE RAL

This paper presents a study on the integral equation method and the Nyst\"{o}m method for the scattering of time-harmonic acoustic waves by a two-layered medium with an unbounded perturbed boundary. The medium consists of two layers separated by a plane interface, for which we assume transmission boundary conditions. We assume either Dirichlet or impedance boundary conditions for the rough surface boundary. Unlike classical rough surface scattering problems, the presence of a plane interface makes it difficult to establish the well-posedness of the scattering problem and to find a numerical treatment. We introduce the two-layered Green function and prove that this function has similar asymptotic decay properties to the half-space Green function. By using a similar approach to classical rough surface problems, we establish the uniqueness of the scattering problem. We derive the integral equation formulations using the two-layered Green function as the integral kernel and use them to prove the existence of the scattering problem. Furthermore, we propose the Nyst\"{o}m method for discretizing the integral equations and establish its convergence. Finally, we perform numerical experiments to demonstrate the effectiveness of the Nyst\"{o}m method., Comment: 44 pages with 3 figures

Traffic forecasting is one of the most fundamental problems in transportation science and artificial intelligence. The key challenge is to effectively model complex spatial-temporal dependencies and correlations in modern traffic data. Existing methods, however, cannot accurately model both long-term and short-term temporal correlations simultaneously, limiting their expressive power on complex spatial-temporal patterns. In this paper, we propose a novel spatial-temporal neural network framework: Attention-based Spatial-Temporal Graph Convolutional Recurrent Network (ASTGCRN), which consists of a graph convolutional recurrent module (GCRN) and a global attention module. In particular, GCRN integrates gated recurrent units and adaptive graph convolutional networks for dynamically learning graph structures and capturing spatial dependencies and local temporal relationships. To effectively extract global temporal dependencies, we design a temporal attention layer and implement it as three independent modules based on multi-head self-attention, transformer, and informer respectively. Extensive experiments on five real traffic datasets have demonstrated the excellent predictive performance of all our three models with all their average MAE, RMSE and MAPE across the test datasets lower than the baseline methods.

This paper presents a study on the integral equation method and the Nystöm method for the scattering of time-harmonic acoustic waves by a two-layered medium with an unbounded perturbed boundary. The medium consists of two layers separated by a plane interface, for which we assume transmission boundary conditions. We assume either Dirichlet or impedance boundary conditions for the rough surface boundary. Unlike classical rough surface scattering problems, the presence of a plane interface makes it difficult to establish the well-posedness of the scattering problem and to find a numerical treatment. We introduce the two-layered Green function and prove that this function has similar asymptotic decay properties to the half-space Green function. By using a similar approach to classical rough surface problems, we establish the uniqueness of the scattering problem. We derive the integral equation formulations using the two-layered Green function as the integral kernel and use them to prove the existence of the scattering problem. Furthermore, we propose the Nystöm method for discretizing the integral equations and establish its convergence. Finally, we perform numerical experiments to demonstrate the effectiveness of the Nystöm method., 44 pages with 3 figures

Additional file 1.

Additional file 2: Table 1. Steinhoff classification.

The COVID-19 pandemic has sparked a global interest in understanding the mechanism of transmission of bioaerosols in enclosed environments. Swift and accurate calculations of particle trajectories are crucial for predicting the diffusion of bioaerosols. The use of machine learning can expedite these calculations and predictions. However, research focusing on the use of machine learning methods for calculating bioaerosol trajectories remains scarce. A bioaerosol trajectory is a time series with long intervals and delays between different positions; certain machine learning models are well suited for handling time series data. Herein, we aimed to establish a new method we refer to as physics–machine learning (P–ML) that includes a machine learning model for calculating bioaerosol trajectories. To this end, we adopted a lightweight, single-layer long short-term memory (LSTM) model and used supervised learning with mean squared error as an evaluation metric for training. Our findings indicate that disregarding the turbulence diffusion enables us to train the LSTM model by a motion equation. Furthermore, the model accurately predicted trajectories while exhibiting some degree of transferability. However, when considering the turbulence diffusion of bioaerosol, the training data in P–ML method could not be generated using a motion equation with turbulence diffusion model (Discrete Random Walk model). To address this issue, we integrating the fluctuating velocity into the LSTM model input. Consequently, the predicted results were consistent with the motion equation. Our method exhibits considerable potential for expediting trajectory calculation and aiding in early warning and rapid design in enclosed environments. Copyright © 2023 American Association for Aerosol Research

Purpose. An inverted ILM flap might be accidentally separated from the retina or sucked away during surgery for large macular holes (MHs). This article is to determine the efficacy of a new inverted pedicled internal limiting membrane (ILM) flap attached to an optic disc with an autologous blood clot (ABC) technique for the treatment of large MHs. Methods. An inverted pedicled ILM flap connected to the optic disc with ABC was used to treat 12 consecutive patients with significant macular holes (>600 m). The ILM was first peeled off around MH as a semidiameter of about 1.5 diameters of the optic disc. The superior residual ILM was used to produce a pedicled ILM flap that was connected to the optic disc and was later inverted to cover the MH. The macular hole was covered with a repositioned flap larger than 2 MH diameters in an inverted way. ABC was used to fasten the flap, followed by fluid-air exchange with air or C3F8 as tamponade. Spectral domain-optical coherence tomography (SD-OCT) and best-corrected visual acuity (BCVA) were performed at each postoperative follow-up. Results. The mean aperture and base macular hole diameters were 737.9 ± 109.6 µm (range, 607–982 µm) and 1244.3 ± 227.4 µm (range, 975–1658 µm). All macular holes (100%) were closed after a single surgery without intraoperative or postoperative complications related to the ILM transposition technique. At the last postoperative visit, we found one eye with a U-shaped closure, three eyes with W-shaped closures, and eight eyes with V-shaped closures. No postoperative flap closures were noted in all cases. The preoperative mean BCVA was 1.5 ± 0.3 (range, 1.1–2.0). After a mean follow-up of 5.3 ± 4.8 (range, 3–16) months, the postoperative mean BCVA was 0.8 ± 0.2 (range, 0.6–1.1), and the difference was statistically significant (p

Additional file 1.

Additional file 4: Table 3. Short Orientation Memory Concentration Test.

Additional file 3: Table 2. Brain relaxation 4-point scale.

Verticilllium wilt of cotton is a devastating soil-borne disease, which is caused by Verticillium dahliae Kleb. Bacillus velezensis strain AL7 was isolated from cotton soil. This strain efficiently inhibited the growth of V. dahliae. But the mechanism of the biocontrol strain AL7 remains poorly understood. To understand the possible genetic determinants for biocontrol traits of this strain, we conducted phenotypic, phylogenetic and comparative genomics analysis. Phenotypic analysis showed that strain AL7 exhibited broad-spectrum antifungal activities. We determined that the whole genome sequence of B. velezensis AL7 is a single circular chromosome that is 3.89 Mb in size. The distribution of putative gene clusters that could benefit to biocontrol activities was found in the genome. Phylogenetic analysis of Bacillus strains by using single core-genome clearly placed strain AL7 into the B. velezensis. Meantime, we performed comparative analyses on four Bacillus strains and observed subtle differences in their genome sequences. In addition, comparative genomics analysis showed that the core genomes of B. velezensis are more abundant in genes relevant to secondary metabolism compared with B. subtilis strains. Single mutant in the biosynthetic genes of fengycin demonstrated the function of fengycin in the antagonistic activity of B. velezensis AL7. Here, we report a new biocontrol bacterium B. velezensis AL7 and fengycin contribute to the biocontrol efficacy of the strain. The results showed in the research further sustain the potential of B. velezensis AL7 for application in agriculture production and may be a worthy biocontrol strain for further studies.

Background: The development of environment-friendly and cost-effective palladium( Pd) based nanocomposite is of high interest for catalytic applications. Objective and Methods: In this paper, a porous Pd/two-dimensional-material (graphene oxide (GO) and reduced graphene oxide (rGO)) nanocomposite was synthesized with a green and facile method, without adding any additional reductant, surfactant and special solvent. Results: The catalytic activity of the Pd/rGO composite was investigated using the 4-nitrophenol (4-NP) reduction reaction in the presence of sodium borohydride (NaBH4). The results showed that the Pd/rGO nanocomposite not only exhibited much higher catalytic activity than the pure porous Pd catalyst but also showed a very good catalytic stability due to the less Pd aggregation and increased local 4-NP concentration arose from rGO bonding attraction. Besides, the Pd-rGO nanocomposite showed a kapp value of 0.383 min-1, which was 13 times higher than the pure Pd (0.0292 min-1), as well as a reliable 4-NP conversion rate of over 97%. Conclusion: This study may provide a route for green-design and synthesis of heterogeneous catalyst composites with lower cost and better performance.

Single-crystal metals are promising substrates for the epitaxial growth of two-dimensional (2D) materials owing to the absence of grain boundaries and distinctive symmetries. The rich arrangements of atoms on various crystal facets serve as an ideal platform for cutting-edge research on regulating the structures of the as-grown 2D materials. However, it is challenging to obtain large single-crystal metal materials, which hinders the in-depth exploration of single-crystal metal-2D material interface interactions. This review provides a critical summary of the recent progress towards achieving large-area single-crystal metals via anomalous grain growth and epitaxial deposition. Then, crucial roles of single-crystal metal substrates in the controlled growth of 2D materials are highlighted by discussing epitaxial growth of single crystals, rapid and low-temperature preparation, and wrinkle elimination. Finally, a perspective into future research on the preparation of single-crystal metals and 2D materials is provided, which is intended to inspire novel growth frontiers for 2D materials.

Paris L. section Axiparis H. Li (Melanthiaceae) is a taxonomically perplexing taxon with considerable confusion regarding species delimitation. Based on the analyses of morphology and geographic distribution of each species currently recognized in the taxon, we propose a revision scheme that reduces the number of species in P. sect. Axiparis from nine to two. To verify this taxonomic proposal, we employed a genome skimming approach to recover the plastid genomes (plastomes) and nuclear ribosomal DNA (nrDNA) regions of 51 individual plants across the nine described species of P. sect. Axiparis by sampling multiple accessions per species. The species boundaries within P. sect. Axiparis were explored using phylogenetic inference and three different sequence-based species delimitation methods (ABGD, mPTP, and SDP). The mutually reinforcing results indicate that there are two species-level taxonomic units in P. sect. Axiparis (Paris forrestii s.l. and P. vaniotii s.l.) that exhibit morphological uniqueness, non-overlapping distribution, genetic distinctiveness, and potential reproductive isolation, providing strong support to the proposed species delimitation scheme. This study confirms that previous morphology-based taxonomy overemphasized intraspecific and minor morphological differences to delineate species boundaries, therefore resulting in an overestimation of the true species diversity of P. sect. Axiparis. The findings clarify species limits and will facilitate robust taxonomic revision in P. sect. Axiparis.

Background Cotton has been increasingly harmed by the mirid bug (Lygus pratensis Linnaeus) in Xinjiang Uyghur Autonomous Region, China. Using trap plants within or around the border of the cotton may be a beneficial management strategy for this pest of cotton. Results The potential of safflower (Carthamus tinctorius Linn) as a trap plant for managing L. pratensis was evaluated in laboratory and field experiments. Y-tube olfactometer assays demonstrated that L. pratensis was highly attracted to volatiles derived from safflower. Field experiments showed that safflower plots hosted more L. pratensis (adults and nymphs) than cotton plots. Early-sown safflower had more L. pratensis than mid-sown or late-sown safflower, and was more conducive to the settlement and reproduction of L. pratensis. The density of L. pratensis on safflower trap crops in three sowing patterns was significantly higher than on adjacent cotton. The pattern of intercropping safflower trap crops was more effective at reducing densities of L. pratensis on cotton than placing safflower as 'spot' trap crops or peripheral trap crops. However, this result may also be related to the overall area of the safflower trap crops. With regular chemical control of L. pratensis on safflower trap crops, the number of cotton bolls was increased by 10.04%, while the rate of boll damage was reduced by 33.44%, compared to cotton without safflower trap crops and insecticide sprays. Conclusion Safflower shows promise as an effective trap crop for L. pratensis, and may contribute to controlling L. pratensis in cotton. This article is protected by copyright. All rights reserved.

It is of great significance to acquire the soil surface roughness accurately for the study of the interaction between tractors and soil. Based on the laser sensor, this paper proposed the non-contact measuring instrument of the soil surface roughness with the data acquiring system by using Lab-View software. By using W-M theory, three commonly used fractal dimension calculation methods are compared and analyzed.. The result showed that the Root-mean-square method has the highest accuracy and clear physical meaning, which is ideal method to calculate the soil surface roughness characteristics. When the fractal dimension is between 1.4 and 1.6, the acquired data is analysed by the Root-mean-square method to obtain the fractal features of the soil surface roughness. The experiment results indicated that the fractal dimension of the ploughed surface is 1.39, that of disc harrow surface is 1.550, and that of rolled surface is 1.46-1.54. Obviously, the fractal dimension can accurately distinguish the soil surface roughness with the different treatments. However, the fractal dimension selected from different scales showed an obvious instability during calculations. The surface roughness index combined with the two parameters can effectively represent the soil surface roughness, and the larger the surface roughness index is, the greater the surface roughness is.

It is of great importance to develop epoxy vitrimers with the combination of high performance and versatile recyclability. Herein, two imine-containing hardeners were synthesized from bio-based vanillin and petroleum-based p-hydroxy benzaldehyde. The epoxy resins cured by these two hardeners show high Tg (>120 °C), tensile strength (>60 MPa), Young’s modulus (>2500 MPa), and good solvent resistance. Owing to the incorporation of imine dynamic covalent bond, the cured epoxy resins are reprocessable and degradable. Notably, the chemical degradation products can be reused to prepare new epoxy resins, thus achieving a closed-loop recycling process. Both the reprocessed and chemically recycled epoxy resins exhibit high-percentage retention of thermal and mechanical properties. Finally, this study demonstrates that the epoxy resin cured by the vanillin-based hardener shows comparable thermal, mechanical, and recycling properties compared with the epoxy resin cured by the petroleum-based counterpart.

Additional file 2. Standardized Process and Indicator Definition.

Achieving realistic, vivid, and human-like synthesized conversational gestures conditioned on multi-modal data is still an unsolved problem due to the lack of available datasets, models and standard evaluation metrics. To address this, we build Body-Expression-Audio-Text dataset, BEAT, which has i) 76 hours, high-quality, multi-modal data captured from 30 speakers talking with eight different emotions and in four different languages, ii) 32 millions frame-level emotion and semantic relevance annotations. Our statistical analysis on BEAT demonstrates the correlation of conversational gestures with facial expressions, emotions, and semantics, in addition to the known correlation with audio, text, and speaker identity. Based on this observation, we propose a baseline model, Cascaded Motion Network (CaMN), which consists of above six modalities modeled in a cascaded architecture for gesture synthesis. To evaluate the semantic relevancy, we introduce a metric, Semantic Relevance Gesture Recall (SRGR). Qualitative and quantitative experiments demonstrate metrics' validness, ground truth data quality, and baseline's state-of-the-art performance. To the best of our knowledge, BEAT is the largest motion capture dataset for investigating human gestures, which may contribute to a number of different research fields, including controllable gesture synthesis, cross-modality analysis, and emotional gesture recognition. The data, code and model are available on https://pantomatrix.github.io/BEAT/., Comment: 28 pages, 15 figures, Accepted by ECCV2022

Additional file 1. SPIRIT 2013 Checklist.

Subduction of oceanic lithosphere is widely considered as the primary cause of mantle heterogeneity as reflected by the chemical variation of ocean island basalts. However, the fate of deeply subducted oceanic lithosphere (i.e., remaining intact, getting segmented or completely destroyed and intermixed with ambient mantle) is still largely unknown. Based on trace element and radiogenic isotope systematics, it has been suggested that the geochemical difference of shield and post-erosional stage lavas of the volcanic Madeira archipelago reflects recycling of different portions of subducted lithosphere (e.g., Geldmacher and Hoernle, 2000, EPSL 183; Gurenko et al. 2013, Lithos 170-171). Accordingly, the geochemical composition of the shield stage magmas reflects altered upper oceanic crust, while the isotopically less enriched post-erosional magmas preferentially stem from less-modified, lower crustal/lithospheric mantle portions of the recycled slab. New, high precision potassium (δ41K of -0.75‰ to -0.50‰) and oxygen (δ18O of 4.90‰ to 5.21‰ in olivine phenocrysts) isotope data from Madeira lavas support this model. Subduction dehydration can cause large K isotope fractionation in the upper, seawater-altered parts of oceanic crust resulting in lighter K isotopes (lower δ41K) in ocean island basalts containing such material. The measured δ41K represents the lowest range among oceanic basalts published so far and overlaps with obducted eclogite, indicating the involvement of dehydrated oceanic crust. The correlation of light K with light O and enriched radiogenic isotope ratios supports the model that Madeira’s magma source contains different portions of subducted oceanic crust, which were preserved over millions of years without significant intermixing.

Additional file 1.

Additional file 1: Supplemental Figure 1. Comparison of Baseline cytokines levels in the aqueous humor among 3 groups. Supplemental Figure 2. Comparison of cytokine levels in the aqueous humor at the beginning of PPV between group I and II. Supplemental Figure 3. Comparison of cytokine levels in the aqueous humor at the beginning of PPV between IOB and INB group.

The roughness of the interlayer concrete, which is an important index for the construction of dams, affects the mechanical properties of the interface between new and old concrete. The traditional monitoring method cannot satisfy field measurements. Therefore, this paper proposes a concrete surface roughness measurement method based on 3D laser scanning technology and implements 3D point cloud calculations. Two layers of specimens with same concrete mix proportion were poured 28 days apart, and a splitting tensile strength test of the superimposed specimen was carried out. Four groups of experiments (MR-S, MR-N, MR-15, and MR-35) tested the interlaminar tensile splitting strength of nine 150 mm cubic specimens on the 3rd, 7th, 14th, and 28th days, respectively. Filling volume, mean amplitude, surface area expansion rate, normal angle std. dev., and curvature std. dev. were measured in the study. The results showed that as the surface roughness of the concrete increased, as did the flushing pressure. The splitting strength of the concrete interface after it solidified increased with age. At 28 days, the splitting strength of MR-15 was higher than that of MR-35. The mean amplitude and the normal angle std. dev. of the rough surface could replace the traditional filling volume index. The new 3D point cloud calculation method for calculating concrete surface roughness was proven by experiments to have good performance.

To ascertain the prevalence of contralateral patent processus vaginalis (CPPV) in life and the significance of the prevalence trends for treatment. We performed a retrospective review of all inguinal hernias (IHs) that underwent repair in our hospital from 2014 to 2018. We analyzed the frequency of occurrence and treatment in boys. We assessed and compared the history, initial sides of hernia, CPPV and prognoses in different age groups. We assessed all IH cases repaired in our hospital and selected male patients of a variety of ages, including boys and men. Recurrent cases were not enrolled. A total of 3243 cases were enrolled: 2489 [right-sided IH 1411 (56.69%) vs. left-sided IH 975 (39.17%), bilateral IH 103 (4.14%)] in children and 754 [right-sided IH 485 (64.32%) vs. left-sided IH 236 (31.30%), bilateral IH 33 (4.38%)] in adults. A total of 1124 CPPVs were identified in children with unilateral IH (2386), and 12 were identified in adults (267) (p 0.05). The incidence of IH in boys was significantly higher than that in men. The number of incident cases declines rapidly with age in boys. The processus vaginalis is normally obliterated and involuted but may instead remain patent for a long period before closure; routine exploration on the contralateral side may eliminate the possibility of spontaneous PPV closure.

Bottom-up based multi-person pose estimation approaches use heatmaps with auxiliary predictions to estimate joint positions and belonging at one time. Recently, various combinations between auxiliary predictions and heatmaps have been proposed for higher performance, these predictions are supervised by the corresponding L2 loss function directly. However, the lack of more explicit supervision results in low features utilization and contradictions between predictions in one model. To solve these problems, this paper proposes (i) a new loss organization method which uses self-supervised heatmaps to reduce prediction contradictions and spatial-sequential attention to enhance networks' features extraction; (ii) a new combination of predictions composed by heatmaps, Part Affinity Fields (PAFs) and our block-inside offsets to fix pixel-level joints positions and further demonstrates the effectiveness of proposed loss function. Experiments are conducted on the MS COCO keypoint dataset and adopting OpenPose as the baseline model. Our method outperforms the baseline overall. On the COCO verification dataset, the mAP of OpenPose trained with our proposals outperforms the OpenPose baseline by over 5.5%.

To reduce the structural failure risk of net cages under extreme sea conditions, this study analysed the yield phenomenon under mooring constraints and excessive or long-term wave loads. The floating collar deforms by shear when a twisted 1 m for the 8-point type and 5 m for the four point type. The structural strength in the Z-vertical direction is one-fifth of that in the X-horizontal direction. The maximum deformation is mainly on the two ends of the cap ned pipes. The critical points of the guardrail may reach the yield stress when the wave height is 1.1 m, while the height of the floating pipe is 5 m. The float can be damaged more easily when there is torsion or shear deformation caused by irregular waves. The results provide guidelines for the optimised structural design of net cages, which by increasing the number of mooring points and cap neds as well as reducing the welding points and structural mutation points, can improve the ultimate bearing capacity and fatigue reliability of the cage float.

Conventional reduction treatment methods for nickel slag show drawbacks such as high energy cost, heavy material burden or secondary pollution. Thus, a novel environmentally friendly reduction treatment method for high-silicon wastes, especially nickel slag, is proposed in this paper. The main characteristic is to lower the alkali–ore ratio (mass ratio of NaOH to ore) through introducing a high-speed premixing procedure before roasting. Optimal process parameters have been found experimentally, i.e., a roasting temperature of 823 K, alkali–ore ratio of 1.6:1, and roasting time of 30 min. The desilication ratio reached to 91.3 wt.%. Compared with previous NaOH roasting processes with stirring, the NaOH consumption is down by 60%, which greatly reduces the material burden. Through carbonation decomposition of the Na2SiO3 solution generated in the NaOH roasting, amorphous silica is recycled as the final product. The proposed method is expected to be a promising method for industrial reduction treatment of nickel slag.

Deep-water fish cage floating collar also referred to as float, bears a load in the form of waves, fishing nets, and moorings, in which the longitudinal wave force is the main type of loading. The long-term continuous effects caused by wave force could cause reduction in strength, or vibration failure in the floating collar. In this study, the peak responses of a single-point mooring (SPM) cage floating collar, due to either static or vibration loadings, were calculated by the finite element method (FEM) based on an elastic model. In this model, the float exhibited macro-plastic deformation when the stress of 26.1 MPa, generated under 100 kN load, was greater than the yield limit (25 MPa). With the increase in order modes from 1 to 18 (1.2–7.9 Hz), the stress increased. Moreover, the harmonic stress corresponding to 8 and 0.1 Hz was clearly higher than that for 0 Hz under 100 kN loads, due to structural resonance. The range of stress values due to the random vibration was 16.0–63.7 MPa, when the angular velocities (k) were in the range of 0.01–16 rad s―1. Moreover, the transient response (34.4 MPa) was maximum when the angular velocity was 10 rad s―1 (range 1–100 rad s―1). The reliability rate of the entire body was 53.1% and 97.0% after 108 loading cycles for 100 kN and 10 kN loads, respectively. Furthermore, the fatigue modes of the key components were determined from the outer triangular tops and inner hexagonal intersections. In short, static analysis, vibration analysis, and fatigue analysis of FEM could be used as reliable ways to evaluate structural strength and failure for floating system. Finally, the floating parts could be strengthened with partially double pipes or optimized by increasing the stiffness, and appropriate damping could be widely used.

The SC200 proton therapy facility is consisting of a superconducting cyclotron, a gantry treatment room and a fixed beam room. The proton beams are transported mainly with beam transport devices, such as dipole magnets, quadrupole magnets, and corrector magnets which lie on the beam transport line layout of which is based on the beam optics design. A series of dipole, quadrupole, and corrector magnets ultimately make high-quality transmission of proton beams possible. Dipole magnets are mainly for beams deflection, quadrupole magnets are for beam focusing, and corrector magnets for orbit correction of beams. This paper shows the design of such magnets for the beam transport line. Besides, main parameters of magnets are presented and magnetic analysis work is also illustrated in this paper. The magnetic fields of dipole and quadrupole magnets are measured by hall mapping system and rotary coil measuring system. The results show that the measuring results are a little worse than the simulation results. However, both methods can meet the design requirement and the basic trend is similar to each other.

Twisted bilayer graphene (tBLG) has recently attracted growing interest due to its unique twist-angle-dependent electronic properties. The preparation of high-quality large-area bilayer graphene with rich rotation angles would be important for the investigation of angle-dependent physics and applications, which, however, is still challenging. Here, we demonstrate a chemical vapor deposition (CVD) approach for growing high-quality tBLG using a hetero-site nucleation strategy, which enables the nucleation of the second layer at a different site from that of the first layer. The fraction of tBLGs in bilayer graphene domains with twist angles ranging from 0° to 30° was found to be improved to 88%, which is significantly higher than those reported previously. The hetero-site nucleation behavior was carefully investigated using an isotope-labeling technique. Furthermore, the clear Moiré patterns and ultrahigh room-temperature carrier mobility of 68,000 cm2 V−1 s−1 confirmed the high crystalline quality of our tBLG. Our study opens an avenue for the controllable growth of tBLGs for both fundamental research and practical applications., The synthesis of twisted bilayer graphene with controllable angles is challenging. Here, the authors devise a chemical vapor deposition approach using a hetero-site nucleation strategy that affords twist angles ranging from 0° to 30°.

Higher magnetic fields are always favoured in the magnetoplasmadynamic thruster (MPDT) due to its superior control of the plasma profile and acceleration process. This paper introduces the world's first integrated study on the 150 kW level AF-MPDT equipped with a superconductive coil. A completely new way of using superconducting magnet technology to confine plasma with high energy and extremely high temperatures is proposed. Using the PIC method of microscopic particle simulation, the plasma magnetic nozzle effect and performance of the MPDT under different magnetic-field conditions were studied. The integrated experiment used demonstrated that, in conjunction with the superconducting coil, greater homogeneity and a stronger magnetic field not only caused more even cathode ablation and improved its lifespan but also improved the performance of the MPDT (maximum thrust was 4 N at 150 kW, 0.56 T). Maximum thrust efficiency reached 76.6% and the specific impulse reached 5714 s.

With the rapid development of artificial intelligence and the advent of the 5G era, deep learning has received extensive attention from researchers. Broad Learning System (BLS) is a new deep learning model proposed recently, which shows its effectiveness in many fields, such as image recognition and fault detection. However, the training process still requires vast computations, and therefore cannot be accomplished by some resource-constrained devices. To solve this problem, the resource-constrained device can outsource the BLS algorithm to cloud servers. Nevertheless, some security challenges also follow with the use of cloud computing, including the privacy of the data and the correctness of returned results. In this paper, we propose a secure, efficient, and verifiable outsourcing algorithm for BLS. This algorithm not only improves the efficiency of the algorithm on the client but also ensures that the clients sensitive information is not leaked to the cloud server. In addition, in our algorithm, the client can verify the correctness of returned results with a probability of almost 1. Finally, we analyze the security and efficiency of our algorithm in theory and prove our algorithms feasibility through experiments.

Speech production is a dynamic procedure, which involved multi human organs including the tongue, jaw and lips. Modeling the dynamics of the vocal tract deformation is a fundamental problem to understand the speech, which is the most common way for human daily communication. Researchers employ several sensory streams to describe the process simultaneously, which are incontrovertibly statistically related to other streams. In this paper, we address the following question: given an observable image sequences of lips, can we picture the corresponding tongue motion. We formulated this problem as the self-supervised learning problem, and employ the two-stream convolutional network and long-short memory network for the learning task, with the attention mechanism. We evaluate the performance of the proposed method by leveraging the unlabeled lip videos to predict an upcoming ultrasound tongue image sequence. The results show that our model is able to generate images that close to the real ultrasound tongue images, and results in the matching between two imaging modalities., Comment: Accepted in KDD Workshop (BIOKDD 2021)

Prior research has documented many benefits associated with team-level psychological safety. However, we know little about the boundary conditions of these findings, particularly how psychological safety operates at the organization level and if and when it is helpful over time. Here, we explore how organization-level psychological safety and another aspect of workplace climate, felt accountability, impacts organizational performance over time. Our study is situated in the New York City public school system, a context rife with uncertainty and calls for change, including immense pressure on teachers to improve student outcomes. Drawing on over 170,000 survey responses from teachers in 545 schools across three years, our multilevel analyses unexpectedly show that psychological safety is not, on its own, “helpful” with regards to organizational performance over time. Indeed, the best combination occurred when psychological safety was relatively low and felt accountability was relatively high. Thus, these two dimensions of workplace climate appear to be interrelated in critical ways over time, albeit unexpectedly. We conclude with implications of our discoveries for future theory-building and research on psychological safety and felt accountability, and we propose new lines of research on the roles of interdependence and attention for studying psychological safety at the organization level.

Chemical vapor deposition is the most promising technique for the mass production of high-quality graphene, in which the metal substrate plays a crucial role in the catalytic decomposition of the carbon source, assisting the attachment of the active carbon species, and regulating the structure of the graphene film. Due to some drawbacks of single metal substrates, alloy substrates have gradually attracted attention owing to their complementarity in the catalytic growth of graphene. In this review, we focus on the rational design of binary alloys, such as Cu/Ni, Ni/Mo, and Cu/Si, to control the layer numbers and growth rate of graphene. By analyzing the elementary steps of graphene growth, general principles are summarized in terms of the catalytic activity, metal–carbon interactions, carbon solubility, and mutual miscibility. Several challenges in this field are also put forward to inspire the novel design of alloy catalysts and the synthesis of graphene films bearing desirable properties.

The rich and complex arrangements of metal atoms in high-index metal facets afford appealing physical and chemical properties, which attracts extensive research interest in material science for the applications in catalysis and surface chemistry. However, it is still a challenge to prepare large-area high-index single crystals in a controllable and cost-efficient manner. Herein, entire commercially available decimeter-sized polycrystalline Cu foils are successfully transformed into single crystals with a series of high-index facets, relying on a strain-engineered anomalous grain growth technique. The introduction of a moderate thermal-contact stress upon the Cu foil during the annealing leads to the formation of high-index grains dominated by the thermal strain of the Cu foils, rather than the (111) surface driven by the surface energy. Besides, the designed static gradient of the temperature enables the as-formed high-index grain seed to expand throughout the entire Cu foil. The as-received high-index Cu foils can serve as the templates for producing high-index single-crystal Cu-based alloys. This work provides an appealing material basis for the epitaxial growth of 2D materials, and the applications that require the unique surface structures of high-index metal foils and their alloys.

Bacillus velezensis AL7, isolated from cotton soil, had strong antagonistic activity to Verticillium dahlia Kleb. The AL7 genome consisted of one chromosome with 3,894,709 bp (46.64% G+C content). Genome annotation predicted 3,706 protein-coding genes, 86 tRNAs, and 27 rRNAs. We sequenced and annotated the complete AL7 genome to help us better understand use of this strain.

Recent advancements in medical entity linking have been applied in the area of scientific literature and social media data. However, with the adoption of telemedicine and conversational agents such as Alexa in healthcare settings, medical name inference has become an important task. Medication name inference is the task of mapping user friendly medication names from a free-form text to a concept in a normalized medication list. This is challenging due to the differences in the use of medical terminology from health care professionals and user conversations coming from the lay public. We begin with mapping descriptive medication phrases (DMP) to standard medication names (SMN). Given the prescriptions of each patient, we want to provide them with the flexibility of referring to the medication in their preferred ways. We approach this as a ranking problem which maps SMN to DMP by ordering the list of medications in the patient's prescription list obtained from pharmacies. Furthermore, we leveraged the output of intermediate layers and performed medication clustering. We present the Medication Inference Model (MIM) achieving state-of-the-art results. By incorporating medical entities based attention, we have obtained further improvement for ranking models.

In this study, a numerical model was established to simulate the dynamic behavior of a floating net cage in waves and current, based on the finite element method. To validate the numerical model, we considered a case based on the motions of the net cage under regular waves and current, where we calculated and compared the simulated results. The comparison of the results indicated good agreement. We calculated the dynamic deformation of the floating collar of the net cage under regular/irregular waves and current, and we analyzed the effects of the net, strong waves and current, and the length of the mooring line on the cage collar deformation. The results indicated that the deformation of the floating collar with a net was much greater than that without a net. The collar deformation became larger as the wave height or current velocity increased. Therefore, in order to reduce the risk of local collar failure due to plastic deformation, adding a casing pipe in the position of the mooring line connection point on the floating collar could greatly enhance the bearing capacity of the cage collar under severe sea conditions. In addition, increasing the length of the mooring line would help to decrease the mooring line tension and further reduce deformation of the cage collar.

The mirid bug Lygus pratensis is an important pest of cotton, and is primarily managed through insecticide application. In this study, conducted in Xinjiang (China), we assessed the relative attractiveness of sunflower (Helianthus annuus) to L. pratensis adults in local cotton plots from 2015-2016 and quantified the associated contribution of inter-planted sunflower strips to suppress field-level L. pratensis populations from 2016-2017. Field-plot trials showed that among six combinations of two sunflower varieties (XKZ6 and SH363) and three planting dates (early-, middle- and late-planted), adult abundance of L. pratensis was highest on early-planted XKZ6 and attained 3.7-5.8 times higher levels than in neighboring cotton plots. In commercial cotton fields, the combined deployment of sunflower strips at field edges and the periodic application of insecticides directed to those strips was found to (1) reduce the mean abundance of L. pratensis population on cotton by 41.9-44.0%, (2) lower the rate of cotton leaf damage by 27.3-30.6% and boll damage by 44.8-46.0%, and (3) increase the number of mature bolls by 7.5%-8.0%. Our work emphasizes how sunflower can be an effective trap crop for L. pratensis and that the establishment of sunflower strips could contribute to its effective and environmentally-sound management in cotton crops.

During the pneumatic conveying process of automatic feeding systems for deep-water off-shore cage culture, blockages of the pipeline and damage to feed pellets can easily occur. To solve these issues, a numerical simulation of the gas-solid two-phase flow of feed pellets in a pipeline was carried out. Based on gas-solid two-phase flow theory, both a computational fluid dynamics (CFD) model and discrete element model were established. Furthermore, solutions of a coupled CFD-DEM simulation were used to analyze the motion of feed pellets within the pneumatic conveying pipeline and changes in the distribution of pellets at various locations from the initial state to steady-state motion were determined. The pressure in the pipeline at different positions is analyzed and compared, and the pressure drop from the inlet of the pipeline to the stable state of particle movement is obtained. The simulation results provide an important basis for the clogging damage mechanism of feed particles and the optimal design of feeding system equipment.

Shapelet is a discriminative subsequence of time series. An advanced shapelet-based method is to embed shapelet into accurate and fast random forest. However, it shows several limitations. First, random shapelet forest requires a large training cost for split threshold searching. Second, a single shapelet provides limited information for only one branch of the decision tree, resulting in insufficient accuracy and interpretability. Third, randomized ensemble causes interpretability declining. For that, this paper presents Random Pairwise Shapelets Forest (RPSF). RPSF combines a pair of shapelets from different classes to construct random forest. It omits threshold searching to be more efficient, includes more information for each node of the forest to be more effective. Moreover, a discriminability metric, Decomposed Mean Decrease Impurity (DMDI), is proposed to identify influential region for every class. Extensive experiments show RPSF improves the accuracy and training speed of shapelet-based forest. Case studies demonstrate the interpretability of our method., Comment: There is some misunderstanding between authors when this manuscript is submitted. Some of authors disagree to submit this manuscript. So we decide to withdraw the article

Despite recent advances, the drug development process continues to face significant challenges to efficiently improve the poor solubility of active pharmaceutical ingredients (API) in aqueous media or to improve the bioavailability of lipid-based formulations. The inherent high intra- and interindividual variability of absorption of oral lipophilic drug leads to inconsistent and unpredictable bioavailability and magnitude of the therapeutic effect. For this reason, the development of lipid-based drugs remains a challenging endeavour with a high risk of failure. Therefore, effective strategies to assure a predictable, consistent, and reproducible bioavailability and therapeutic effect for lipid-based medications are needed. Different solutions to address this problem have been broadly studied, including the approaches of particle size reduction, prodrugs, salt forms, cocrystals, solid amorphous forms, cyclodextrin clathrates, and lipid-based drug delivery systems such as self-emulsifying systems and liposomes. Here, we provide a brief description of the current strategies commonly employed to increase the bioavailability of lipophilic drugs and present Advanced Lipid Technologies® (ALT®), a combination of different surfactants that has been demonstrated to improve the absorption of omega-3 fatty acids under various physiological and pathological states.