bluuebunny/crossref_metadata_2025 huggingface dataset:
Electron-beam induced damage process for Ca2Na2Nb5O16 nanosheets
Authors: Choi Haneul , Lee Gwangyeob , Roh Jong Wook , Park Jin-Woo , Chang Hye Jung
Published: April 2022

Dielectric two-dimensional oxide nanosheets are attractive because of their thermal stability and high-k property. However, their atomic structure characterization has been limited since they are easily degraded by electron-beams. This study aimed to investigate the electron-beam induced damage mechanisms for exfoliated Ca2Na2Nb5O16 (CNNO) nanosheets. Knock-on damage dominantly occurred at high voltages, leaving short-range order in the final amorphous structure. On the other hand, a series of chemical reactions predominantly occurred at low voltages, resulting in random elemental loss and a fully disordered amorphous structure. This radiolysis was facilitated by insulated CNNO nanosheets that contained a large number of dangling bonds after the chemical solution process. The radiolysis damage kinetics was faster than knock-on damage and induced more elemental loss. Based on our understanding of the electron beam-induced degradation, atomic-scale imaging of the CNNO nanosheets was successfully performed using Cs-corrected scanning transmission electron microscopy at 300 keV with a decreased beam current. This result is of particular significance because understanding of electron-beam damage in exfoliated and insulating 2D oxide sheets could improve identification of their atomic structure using electron microscopy techniques and lead to a practical guide for further extensive characterization of doped elements and layered structures to improve their properties.
Tunable synthesis of dendritic fibrous nano silica using 1-pentanol-water microemulsion at low oil to water ratio
Authors: Liu Xuexue , Zhang Xiang , Chen Jian , Zhang Changhao , Feng Songke , Zhang Weiguo
Published: April 2022

Dendritic fibrous nanosilica (DFNS) is a suitable nano-carrier for loading pesticides with radially oriented pores and a large surface area. The microemulsion method is standard method to prepare DFNS, and 1-pentanol is taken to replace cyclohexane as an oil solvent due to its high stability and nontoxic property. The results showed that the volume ratio of 1-pentanol (oil) to water (O/W) and the molar ratio of hexadecyltrimethylammonium bromide (CTAB) to tetraethylorthosilicate (TEOS) had effected on morphology and adsorption properties of DFNS in the water-CTAB-1-pentanol-ethanol-trimethylbenzene (TMB) microemulsion system. DFNS with bicontinuous concentric lamellar morphologies can be synthesized in this microemulsion at the meager O/W volume ratio (0.025–0.045). It features a tight mesoporous structure with a thin dendritic fibrous in 0.03 to 0.04 O/W volume ratio. The particle sizes, surface areas, and porosity of DFNS were positively correlated with the addition of the silica precursor TEOS. The size of DFNS increased from 123 to about 220 nm with the CTAB/TEOS molar ratio decreasing from 0.119 to 0.050. When the molar ratio of CTAB to TEOS  = 0.119, DFNS has a smaller particle size (123 nm) with a larger surface area and abundant honeycomb mesopores; the low O/W volume ratio strategy provides theoretical support for the industrialization development of DFNS and nano-pesticides, which plays a profound role in promoting the sustainable development of pesticide reduction, efficiency and green agriculture.
A generalized image quality improvement strategy of cone-beam CT using multiple spectral CT labels in Pix2pix GAN
Authors: Jiang Yangkang , Zhang Yibao , Luo Chen , Yang Pengfei , Wang Jing , Liang Xiaokun , Zhao Wei , Li Rencang , Niu Tianye
Published: April 2022

Objective. The quantitative and routine imaging capabilities of cone-beam CT (CBCT) are hindered from clinical applications due to the severe shading artifacts of scatter contamination. The scatter correction methods proposed in the literature only consider the anatomy of the scanned objects while disregarding the impact of incident x-ray energy spectra. The multiple-spectral model is in urgent need for CBCT scatter estimation. Approach. In this work, we incorporate the multiple spectral diagnostic multidetector CT labels into the pixel-to-pixel (Pix2pix) GAN to estimate accurate scatter distributions from CBCT projections acquired at various imaging volume sizes and x-ray energy spectra. The Pix2pix GAN combines the residual network as the generator and the PatchGAN as the discriminator to construct the correspondence between the scatter-contaminated projection and scatter distribution. The network architectures and loss function of Pix2pix GAN are optimized to achieve the best performance on projection-to-scatter transition. Results. The CBCT data of a head phantom and abdominal patients are applied to test the performance of the proposed method. The error of the corrected CBCT image using the proposed method is reduced from over 200 HU to be around 20 HU in both phantom and patient studies. The mean structural similarity index of the CT image is improved from 0.2 to around 0.9 after scatter correction using the proposed method compared with the MC-simulation method, which indicates a high similarity of the anatomy in the images before and after the proposed correction. The proposed method achieves higher accuracy of scatter estimation than using the Pix2pix GAN with the U-net generator. Significance. The proposed scheme is an effective solution to the multiple spectral CBCT scatter correction. The scatter-correction software using the proposed model will be available at: https://github.com/YangkangJiang/Cone-beam-CT-scatter-correction-tool.
Dry reforming of methane in a nanosecond repetitively pulsed discharge: chemical kinetics modeling
Authors: Zhang Li , Heijkers Stijn , Wang Weizong , Martini Luca Matteo , Tosi Paolo , Yang Dezheng , Fang Zhi , Bogaerts Annemie
Published: April 2022

Nanosecond pulsed discharge plasma shows a high degree of non-equilibrium, and exhibits relatively high conversions in the dry reforming of methane. To further improve the application, a good insight of the underlying mechanisms is desired. We developed a chemical kinetics model to explore the underlying plasma chemistry in nanosecond pulsed discharge. We compared the calculated conversions and product selectivities with experimental results, and found reasonable agreement in a wide range of specific energy input. Hence, the chemical kinetics model is able to provide insight in the underlying plasma chemistry. The modeling results predict that the most important dissociation reaction of CO2 and CH4 is electron impact dissociation. C2H2 is the most abundant hydrocarbon product, and it is mainly formed upon reaction of two CH2 radicals. Furthermore, the vibrational excitation levels of CO2 contribute for 85% to the total dissociation of CO2.
Experimental and simulation studies of SCIF considering non-uniform critical current
Authors: Zhou Benzhe , Wang Lei , Wang Kangshuai , Qin Lang , Wang Yaohui , Zhang Zili , Liu Jianhua , Wang Qiuliang
Published: April 2022

As an effective and reliable method of obtaining extremely high magnetic fields, rare-earth barium copper oxide (REBCO) magnets have contributed significantly to the development of condensed matter physics, chemistry, life sciences, and materials research. However, large screening currents in REBCO magnets can significantly degrade the magnetic field quality. Recent experiments on the inner insert of a 30 T superconducting magnet at the Institute of Electrical Engineering, Chinese Academy of Sciences showed that the measured magnetic field is highly asymmetric single-peaked field instead of the designed saddle-shaped fields, and it differs significantly from the values calculated based on the commonly-used uniform and symmetric screening current model. Therefore, a simulation model based on the T–A formulation with consideration of accurate dimensions and critical currents was developed. The simulation results with this new developed model indicate that the angle dependence can cause more than an 8.3% difference in the critical currents of the symmetrically located double pancake (DP) coils of the magnet. The average relative error between the measured and calculated magnetic field values was sharply reduced by a maximum of 44.4% after considering the non-uniform critical currents. In consideration of manufacturing uncertainties and non-uniform critical currents, better magnetic field quality of REBCO magnets can be achieved by arranging the location of each DP with this model.
A closed-loop high temperature superconducting magnet energized by flux pump and its piecewise semi-analytical solution
Authors: Zhu Lingfeng , Wang Yinshun , Zhang Xindan , Wang Lecheng
Published: April 2022

High temperature superconducting (HTS) magnets energized by flux pumps can carry heavy current without heat leakage from current leads and are therefore appropriate for a wide range of applications. However, the soldering resistance remains an obstacle to the persistent operations of the HTS magnets. Here, we propose a closed-loop HTS magnet magnetized by flux pump with thermal switches. The magnet consists of a closed-loop single pancakes (SPs) coil wound by a rare-earth barium copper oxide (REBCO) tape on which a slit is cut to form a closed-loop ring within which current can flow without encountering the soldering resistance. Another REBCO tape is soldered on the closed-loop ring to form a pump bridge and a flux pump consists of a copper coil with iron core is installed around the pump bridge. There exists a group of manganese copper wires wound on the closed-loop ring and the pump bridge respectively as thermal switches. A piecewise semi-analytical solution is suggested to investigate the charging process by which the transport current in the magnet is calculated. Experiments are carried out to verify the feasibility of the magnet and the solution. The results show that the magnet can be operated in a persistent current mode, and thus, this study represents a practical solution for persistent operation of the HTS magnets. Besides, the proposed solution can effectively explain and predict the saturation current of the suggested magnet, which can, therefore, guide the design of other forms of HTS magnets and flux pumps.
An efficient approach for superconducting joint of YBCO coated conductors
Authors: Huang Daxing , Shang Hongjing , Xie Bowei , Zou Qi , Dong Hao , Wang Kai , Zhang Lin , Gu Hongwei , Ding Fazhu
Published: April 2022

Superconducting joints are crucial for second generation high-temperature superconducting (2G HTS) closed-loop coils that work in the persistent current mode (PCM) operation. Here, we report an efficient approach for superconducting joints of YBa2Cu3O7-σ
(YBCO) coated conductors (CCs). The YBCO layer is etched to and from some microchannels, which serve as oxygen diffusion paths during oxygenation annealing (OA), to accelerate the recovery of critical current (I
c) of the joined two YBCO layers. The I
c of the superconducting joint is 118 A at 77 K with an optimized joining temperature and a short OA time (10 h), which is about 82% I
c of the joined YBCO CCs. The persistent field decay of the closed-loop coil shows a joint resistance (R
j) of less than 2.2 × 10−13 Ω at 77 K. Two YBCO films epitaxially grown along the c-axis diffuse into each other at the interface and form a dense joining, enabling superconducting current path. This superconducting joint technique can promote the achievement of the PCM operation in 2G HTS magnet applications, such as magnetic resonance imaging and nuclear magnetic resonance.
A first-principles study of structural, electronic and optical properties of α-Te tubular nanostructures modulated by uniaxial strain
Authors: Yang Riyi , Chen Yu-Yo , Guo Yanrong , Shen Hong , Wang Songyou , Jia Yu , Su Wan-Sheng
Published: April 2022

First-principles calculations were performed to study the effect of uniaxial strain on the electronic properties of α-Te nanotubes (NTs) of different configurations and tube sizes. Our ab initio molecular dynamics simulation and phonon dispersion calculation indicate that both armchair (5, 5) and zigzag (10, 0) α-Te NTs are thermodynamically stable and exhibit good dynamic stability at room temperature. Under compressive and tensile strains of ±10%, the atomic structure of the α-Te NTs remains stable, demonstrating they have good flexibility. An increase in uniaxial strain leads to a progressive decrease in the band gap for both armchair and zigzag α-Te NTs. Interestingly, it is found that armchair (5, 5) α-Te NTs experience an intriguing semiconductor–metal transition at a critical strain, while other α-Te NTs are semiconducting with an adjustable band gap. In addition, the valence band maximum and conduction band minimum charge density between the interlayers has an impact on the type of band gap in the (5, 5) and (10, 0) NTs. Finally, we found the optical properties can be significantly modulated under strain in the z direction. Increasing our understanding of the electronic and optical properties of α-Te NTs under strain modulation helps shed light on the properties of new nanomaterials more generally, paving the way for future optoelectronic applications. These findings highlight the tunable electronic and optical properties of α-Te NTs, which is promising for applications in nanodevices such as opto-electronics, electrical switches, and nanoscale strain sensors.
Direct laser writing regimes for bulk inscription of polarization-based spectral microfilters and fabrication of microfluidic bio/chemosensor in bulk fused silica
Authors: I Kudryashov Sergey , Danilov Pavel A , Rupasov Alexey E , Smayev Mikhail P , Smirnov Nikita A , Kesaev Vladimir V , Putilin Andrey N , Kovalev Michael S , Zakoldaev Roman A , Gonchukov Sergey A
Published: April 2022

Laser inscription of form-birefringent nanograting layers inside fused silica by ultrashort (femto-picosecond) laser pulses at 515 nm was studied as a function of laser, average power and pulsewidth in terms of fabrication regimes. Retardance magnitudes were acquired for single birefringent layers inscribed at different laser parameters, enabling fabrication of polarization-based spectral micro-filters in the form of few-layer microdevices and of microfluidic multi-color refractive-index chemo/biosensor.
Scans-to BIM for the Cultural Heritage: first results of a study case for a medieval church and its urban context
Authors: Grazia D’Urso Maria , Valdambrini Noemi , Marana Barbara , Manzari Valerio
Published: April 2022

Raw data, first acquired by several and integrated geomatic procedures and subsequently processed so as to achieve a 3D geometrical model, are the basis for conservation and preventive maintenance of the Cultural Heritage; furthermore, they also allow for the employment of the BIM, Building Information Modeling methodology. By using point clouds elaborated by terrestrial laser scans this research has as main objective the implementation of the BIM technology for the digitalization of the built heritage. In particular a digital three-dimensional model of the medieval S. Maria della Libera Church in Aquino, in the Southern Lazio has been obtained; it represents all the fundamental construction features of the building, the decorative elements and its localization inside a territorial context rich of history and of historical-artistic-archaeological relevance.
Research on Point Cloud Registration Algorithm Based on Boundary Harris-3D Points and 4PCS
Authors: Xu Zhiwei , Wang Di
Published: April 2022

Point cloud registration based on the 4PCS+ICP algorithm will lead to many problems such as large registration error, low efficiency, and unstable running time, especially when it encounters large point cloud data, these problems will be more prominent, which greatly limits the application of the algorithm. Based on these shortcomings, we propose an optimized registration algorithm, called BH4PCS, to improve the applicability of the 4PCS algorithm. In our method, we first extract the boundary Harris-3D points through the edge detection algorithm and Harris-3D key point extraction method, then we use the 4PCS algorithm for point cloud coarse registration, and finally use KD-ICP to speed up the fine registration. After experimental verification and comparison with the existing artworks, our proposed algorithm registers the larger point cloud model by only using a small number of data points, optimizing the registration efficiency, accuracy, and operation stability of the 4PCS + ICP registration method, and has good robustness to outliers.
The single train’s punctual and energy-saving operation scheme based on dynamic programming algorithm
Authors: Ding Yong , Wang Tiesheng , Zhang Kexin , Chen Jie
Published: April 2022

A punctual and energy-saving operation model and some principles to realize energy-saving operation for train are analysed in this paper in order to reduce the energy consumption and obtain the energy-saving speed curve. According to the basic principles of dynamic programming algorithm, the train operation line is discretized. We reduce the space of state variables by using the maximum capacity operation curve and average speed operation curve. And the cost function for energy and time consumption is constructed according to requirements for punctual and energy-saving operation of trains. The simulation results using specific parameters show that the dynamic programming algorithm using reduced state space has high computational efficiency and effectively reduces the energy consumption of train operation.
Mask wearing detection algorithm based on improved YOLOv4
Authors: Ye Qing , Zhao Yuqi
Published: April 2022

Since the outbreak of COVID-19, the domestic situation has gradually improved, but small-scale outbreaks are still frequent, the current situation of COVID-19 cannot be eased up. Using target detection algorithms to identify mask wearing to remind people to pay attention to the epidemic, can reduce the probability of cross infection in public places. YOLOv4 is a real-time target detection algorithm with fast detection speed and small size, but it has problems such as insufficient positioning of the bounding box and easy to miss the occluded targets. Based on this, we improve the algorithm and integrates the CBAM attention module into the backbone network. At the same time, the depthwise over-parameterized convolution (DO-Conv) is used to replace the ordinary convolution, which improves the network fitting ability without adding additional parameters. The experimental results show that the improved algorithm has improved the positioning accuracy of the bounding box and detection accuracy.
Data Analysis Methods of Natural Fragment Spatial Distribution
Authors: Lv Juan , Kang Zhenyu , Li Yuwen , Yuan Shuqiang , Cheng Xiangyu , Du Juan
Published: April 2022

This paper aims to explore the simulation method of random spatial distribution of natural fragments. The transformation between three-dimensional spatial coordinates and two-dimensional planar coordinates of fragments is realized by coordinate mapping and inverse mapping, and the random uniform distribution of fragments in the two-dimensional plane is realized by the Monte Carlo stochastic points method, so as to obtain the spatial position distribution of fragments.
Research on power load forecasting algorithm of power system based on artificial firefly
Authors: Chen Haomin , Liang Jinzhao
Published: April 2022

The power system is constantly upgraded with the development of information technology. The digital management of power system effectively improves the operation and maintenance efficiency of power system. Although the current power system algorithms have made great progress, there has been no effective prediction algorithm in the field of load forecasting. Load forecasting is a key operation and planning approach of power system. It affects many decisions of power system, such as economic dispatching, automatic generation control, safety evaluation, maintenance dispatching and energy commercialization [1]. In view of the above problems, the power load forecasting algorithm of power system based on artificial firefly will be studied. In the existing resource management framework of power system digital grid platform, the power load business of power system is studied. The artificial firefly algorithm is used to complete the research of power load forecasting algorithm. Simulation results show that the established algorithm has good time complexity and space complexity, and the accuracy of power load forecasting results is improved by at least 22.8%.
A self-supervised feature selection algorithm for spectral embedding based on block HSIC lasso
Authors: Guo Yajing , Duan Lijuan , Xie Chenyao , Zhang Wenbo
Published: April 2022

With the rapid development of information technology, a large amount of unlabeled high-dimensional data has been generated. To be able to better handle these data, we propose a new self-supervised feature selection algorithm for spectral embedding based on block HSIC lasso (FSSBH). It innovatively applies the HSIC theoretical approach to unlabeled scenarios for feature importance assessment, and performs feature selection by self-supervised learning with the pseudo-label matrix formed by the spectral embedding. The algorithm is compared with five popular algorithms for classification experiments on seven publicly available datasets. The results show the superior performance of the FSSBH algorithm.
Video behavior recognition algorithm based on two-stream heterogeneous convolutional neural network
Authors: Ye Qing , Liang Zhenghao
Published: April 2022

In video behavior recognition, making full use of the spatio-temporal information contained in video frame is the critical point to further improve the recognition accuracy. In our study, we propose a video behavior recognition algorithm based on two-stream heterogeneous network, so that we can further extract the spatio-temporal feature information in the video frame, and finally take full advantage of the spatio-temporal features in the video sequence. In view of the characteristics of RGB and optical flow images, this paper uses DenseNet121 and Inception-V4 to structure a two-stream network, to fully extract the spatio-temporal feature information in the video. In this paper, UCF101 dataset is used to evaluate the algorithm, and the recognition accuracy is 91.7%, which verified the reliability of the proposed algorithm.
An application analysis method based on Clustering
Authors: Duan Rui , Chen Junde
Published: April 2022

Depending upon the load intensity and time variation information, we established the indicator system to analyze the of commercial halls, so that the further optimization actions can be taken in practical application scenarios. The representative clustering algorithms including the k-means and AC algorithm are chosen for the comparative analysis, and on this basis, an enhanced k-means algorithm is put forward in this study because the traditional method is sensitive to the initial clustering centroids and lacks the stability. A series of experiments are performed in this work, and the experimental findings reveal the validity of the proposed method. It provides a new idea for the efficiency analysis of commercial halls.
Landslide Hazard Identification Based on Deep Learning and Sentinel-2 Remote Sensing Imagery
Authors: Xia Jun , Liu Hongjiang , Zhu Linfu
Published: April 2022

Landslide is one of the common geological disasters, which seriously threatens human life and property safety. It is particularly important to quickly identify landslide information. This paper takes the Wenchuan earthquake landslide area as the research area, and uses 7 deep learning methods(4-Layer-CNN, AlexNet, ResNet152V2, DenseNet201, InceptionV3, Xception and InceptionResNetV2) to discuss landslide detection methods based on Sentinel-2 remote sensing images. Using the marked landslide and non-landslide sample points, the Sentinel-2 remote sensing image was sliced into 80×80 pixel tiles, and then the deep learning method was used for model training, verification and testing. The results show that : (1) Among the 7 deep learning models, the F1-Score of the DenseNet201 model is the largest, reaching 0.8872, and the RMSE is the smallest 0.2503. It can be seen that the DenseNet model has a good recognition effect on landslide samples, with an accuracy of 0.9172; (2) Second It is InceptionResNetV2, the F1-Score is 0.8721, the RMSE is 0.2721, and the landslide sample recognition accuracy is 0.9012; (3) the worst effect is AlexNet, the minimum F1-Score is only 0.7263, the maximum RMSE is 0.4022, and the accuracy is 0.8295. It can be seen that the deep learning method is applied to Sentinel-2 remote sensing images for landslide image detection, and the accuracy can reach 91.72%, which can quickly and accurately identify landslide information, and improve the method reference and decision basis for disaster prevention and mitigation.
An Effective Approach for Sonar Image Recognition with Improved Efficientdet and Ensemble Learning
Authors: Du Yunben , Lin Wei , Zhong Weibo , Yuan Yu
Published: April 2022

Precisely recognition of underwater targets plays a critical role in the field of underwater unmanned exploration. According to the characteristics of sonar image, in order to improve the accuracy of underwater automatic target recognition, this paper proposes an underwater target sonar image recognition method combined with improved Efficientdet and ensemble learning. According to the regional dominance principle and threshold segmentation method, the sonar image is preprocessed, and preliminary effective features extracted from preprocessed data by Efficientnet backbone, so as to balance the efficiency and power consumption of the algorithm. The feature fusion adopts the improved weighted bi-directional feature pyramid ( BiFPN ) structure to aggregate the global information and strengthen the feature representation of the shallow feature map, which optimizes the problem that the small feature extraction is not ideal due to the low resolution of the sonar image and less detail information. By building a two-level classifier to complete the learning task in an ensemble way, a better classification effect is obtained than a single classifier. This method is applied to the underwater intelligent perception group of the 10th National Marine Aircraft Design and Production Competition in 2021, and won the first prize in the country. The experimental results show that the designed ensemble network model is more accurate than the conventional convolution neural network in identifying underwater targets on the measured sonar image data set while ensuring a certain prediction speed.
Research On Machining Product Quality Prediction Based On Machine Learning
Authors: Lan Chen , Fei Wan
Published: April 2022

Data empowerment has attracted widespread attention from manufacturing companies. Enterprises control the production process by mining the data generated in the processing process, so as to achieve the purpose of improving product quality. This paper mainly uses the classification algorithm in data mining to model the data in the processing process and predict the product quality. Using the accuracy of the model prediction as the evaluation standard, the ID3, CART, SVM, KNN and Adaboost algorithms are compared. The experimental results show that the Adaboost classifier is significantly better than other algorithms in the evaluation index of accuracy, so the Adaboost classifier is selected as the final classifier.
Feature Sharing Attention 3D Face Reconstruction with Unsupervised Learning from In-the-Wild Photo Collection
Authors: Yang Xiaoxiao
Published: April 2022

3D face reconstruction is an active research topic in the field of computer vision research. It has a wide range of application scenarios. The number of 3D face annotation samples is small and the accuracy of the 3D reconstruction algorithm is insufficient. In this paper, we propose a shared attention module and a feature point constraint mechanism, and proposes a 3D face reconstruction algorithm that takes a single face image as input and uses a encoder-decoder network to predict the 3D face. The prediction view and light network introduces the attention mechanism module, which can improve the feature extraction ability of the network. The albedo and depth introduces shared features to help extract richer facial feature information. At the same time, the self-monitoring method of single image input avoids the high requirements of traditional methods for datasets. We conducted comparative experiments and ablation experiments on the BFM, and CelebA face datasets. The experimental results show that compared with Unsup3d and other representative 3D Face reconstruction algorithms, it has a certain improvement in the two evaluation indexes of Scale Invariant Depth Error (SIDE) and Mean Angle Deviation (MAD).
Model Reference Adaptive Speed Observer Control of Permanent Magnet Synchronous Motor Based on Single Neuron PID
Authors: Liu Hao , Zhang Huixian , Zhang He , Chen Gaoqi
Published: April 2022

For the speed sensorless control of permanent magnet synchronous motor (PMSM), a design method based on model reference adaptive observer and single neuron PID speed loop was proposed. In this method, the model reference adaptive observer is used to identify the speed online, the Popov hyperstability is used to determine the reference adaptive law of the speed observer, the neural network module is used to control the q-axis current, and the LMS algorithm is selected to modify the weights of the neural network speed loop online. The simulation results show that the model reference adaptive speed observer control of PMSM based on single neuron PID is effective and robust.
Improved PD of LESO quadrotor control algorithm
Authors: Liu Chunling , Feng Jinlong
Published: April 2022

Aiming at the attitude instability problem caused by the quadrotor’s nonlinearity, strong coupling and susceptibility to external interference, a linear extended state observer (LESO) controller with improved PD was designed. First, the incomplete differential control is formed by adding a first-order inertia system to the differential Elements of the PD algorithm. Then, LESO is used to estimate and compensate the internal and external disturbances in the control system to the original system, which can not only reduce system errors, but also enhance the anti-interference ability of the control system. The MATLAB simulation shows that the improved PD of LESO controller can quickly reach a stable state, effectively improve the stable control ability of the quadrotor’s attitude, with smaller overshoot and better control effect.
Design of interval type-2 fuzzy fractional order PID controller based on particle swarm optimization
Authors: Wu Hao , Zhao Taoyan
Published: April 2022

In this paper, an interval type-2 fuzzy fractional order PID controller (IT2F-FOPIDC) based on particle swarm optimization is proposed. The proposed controller has two adjustable degree of freedom parameters, so the control range of the controller parameters becomes larger and can control the controlled object more flexibly. Aiming at the difficult problem of many controller parameters and tuning, this paper introduces particle swarm optimization algorithm to optimize the controller parameters. In order to avoid the problems of long iteration time and high computational cost caused by Karnik-Mendel reduction algorithm, the enhanced iterative with stop condition algorithm is selected for the proposed controller. Finally, the proposed controller is applied to the second order systems with time delays. Simulation results show that the proposed strategy has faster response time and smaller oscillation amplitude, and its performance is better than fuzzy controller and interval type-2 fuzzy controller.
Optical angular momentum in atomic transitions: a paradox
Authors: Barnett Stephen M , Speirits Fiona C , Babiker Mohamed
Published: April 2022

Stated simply the paradox is as follows: it is clear that the orbital angular momentum of a light beam in its direction of propagation is an intrinsic quantity, and therefore has the same value everywhere in the beam. How then can a Gaussian beam, with precisely zero orbital angular momentum, drive a (single-photon) quadrupole transition which requires the transfer of angular momentum 2ℏ to an absorbing atom?
Engineered assistive materials for 3D bioprinting: support baths and sacrificial inks
Authors: Brunel Lucia G , Hull Sarah M , Heilshorn Sarah C
Published: April 2022

Three-dimensional (3D) bioprinting is a promising technique for spatially patterning cells and materials into constructs that mimic native tissues and organs. However, a trade-off exists between printability and biological function, where weak materials are typically more suited for 3D cell culture but exhibit poor shape fidelity when printed in air. Recently, a new class of assistive materials has emerged to overcome this limitation and enable fabrication of more complex, biologically relevant geometries, even when using soft materials as bioinks. These materials include support baths, which bioinks are printed into, and sacrificial inks, which are printed themselves and then later removed. Support baths are commonly yield-stress materials that provide physical confinement during the printing process to improve resolution and shape fidelity. Sacrificial inks have primarily been used to create void spaces and pattern perfusable networks, but they can also be combined directly with the bioink to change its mechanical properties for improved printability or increased porosity. Here, we outline the advantages of using such assistive materials in 3D bioprinting, define their material property requirements, and offer case study examples of how these materials are used in practice. Finally, we discuss the remaining challenges and future opportunities in the development of assistive materials that will propel the bioprinting field forward toward creating full-scale, biomimetic tissues and organs.
Microwave photonics applications of stimulated Brillouin scattering
Authors: M K Varun , Mishra Akhileshwar , Pant Ravi
Published: April 2022

Generation, processing, and sensing of microwave signals using photonic technologies offer immunity from electromagnetic interference, allow high-speed operation over a wide frequency range, and reduce the overall system weight. Recent developments in integrated photonic technologies further increase the attractiveness of photonics-based radio frequency (RF) systems. Stimulated Brillouin scattering (SBS), due to its inherently narrow bandwidth, wavelength transparent nature, low threshold, and bandwidth reconfigurability, has emerged as a potential contender for microwave photonic (MWP) generation and signal processing. In this article, we present a review of recent developments in the area of SBS-based MWP. We discuss different SBS-based techniques for realizing some of the key MWP signal processing functionalities such as RF generation, filtering, and true time delay. Implementation of these tasks using fiber and on-chip platforms is presented along with the effect of system parameters such as dispersion on their performance. Novel architectures to mitigate these impairments are discussed.
STMP at 10: shaping surface metrology, measurement and phenomena for a decade
Authors: Wood Robert , Costa Henara Lillian
Published: April 2022

Surface Topography: Metrology and Properties (STMP) is reaching its 10th Birthday soon and this paper looks at the inception of the journal and the goals set in the mid 2010s and will look back at what it has published in the most highly cited areas and detail future initiatives to serve the readership. STMP publishes the latest physics, chemistry, life science, materials science and engineering research on applied, functional surfaces. It has published ground-breaking work on surface design, measurement, instrumentation, manufacturing, functionality and modelling as well as cross-disciplinary work on surface and interface engineering across an array of different applications. It is the home of papers from the biannual international conference on Metrology and Properties of Surfaces series. The journal was awarded it’s first impact factor in 2017 and has a current value of 2.038 (2020) and is now working to improve on this. A new initiative for 2021 is to offer a collection of papers from emerging leaders within the scope of the journal.
The TOX subfamily: all-round players in the immune system
Authors: Han Jiawen , Wan Minjie , Ma Zhanchuan , He Ping
Published: April 2022

The thymocyte selection-related HMG box protein (TOX) subfamily comprises evolutionarily conserved DNA-binding proteins, and is expressed in certain immune cell subsets and plays key roles in the development of CD4+ T cells, innate lymphoid cells (ILCs), T follicular helper (Tfh) cells, and in CD8+ T-cell exhaustion. Although its roles in CD4+ T and natural killer (NK) cells have been extensively studied, recent findings have demonstrated previously unknown roles for TOX in the development of ILCs, Tfh cells, as well as CD8+ T-cell exhaustion; however, the molecular mechanism underlying TOX regulation of these immune cells remains to be elucidated. In this review, we discuss recent studies on the influence of TOX on the development of various immune cells and CD8+ T-cell exhaustion and the roles of specific TOX family members in the immune system. Moreover, this review suggests candidate regulatory targets for cell therapy and immunotherapies.
Common colonic community indicators of the suckling pig microbiota where diversity and abundance correlate with performance
Authors: Lee Adam , Le Bon Melanie , Connerton Ian F , Mellits Kenneth H
Published: April 2022

The primary objective of this study was to investigate if common colonic community indicators could be identified from the microbiota of 22-day-old suckling pigs in repeated small-scale trials. A total of three separate trials were conducted at different times in the same year and facility with genetically similar animals. Colonic samples were collected from four pigs in each trial and the microbiome composition assessed by 16s rRNA gene sequencing. Pig weight, average daily gain (ADG), bacterial diversity, and abundance were not significantly different between repeated trials, except for a significant difference in Jaccard Similarity. At genus level, the most abundant taxa identified were Porphyromonadaceae unclassified (15.81%), Ruminococcaceae unclassified, (12.78%), Prevotella (7.26%), Clostridiales unclassified (6.99%), Lactobacillus (6.58%), Phascolarctobacterium (6.52%), and Firmicutes unclassified (5.69%). The secondary objective was to establish if pooled data in terms of microbial diversity and abundance of the colonic microbiota related to weight and ADG. Pig weight at day 22 and ADG positively correlated with α-diversity. Abundance of potential protein digesting and short-chain fatty acid producing operational taxonomic units ascribed to Terrisporobacter, Ruminococcaceae unclassified, Intestinimonas, and Dorea correlated with weight and ADG, suggesting a nutritional role for these common colonic community microbiota members in suckling pigs.
Identification of novel split-GAL4 drivers for the characterization of enteroendocrine cells in the Drosophila melanogaster midgut
Authors: Holsopple Jessica M , Cook Kevin R , Popodi Ellen M
Published: April 2022

The Drosophila melanogaster midgut is commonly studied as a model epithelial tissue for many reasons, one of which is the presence of a diverse population of secretory cells called enteroendocrine cells. Subpopulations of these cells secrete various combinations of peptide hormones which have systemic effects on the organism. Many of these hormones are also produced in the Drosophila brain. The split-GAL4 system has been useful for identifying and manipulating discrete groups of cells, but previously characterized split-GAL4 drivers have not driven expression in high proportions of enteroendocrine cells. In this study, we screened candidate split-GAL4 drivers for enteroendocrine cell expression using known reference drivers for this cell type and discovered a new split-GAL4 driver pair that confers expression in a greater number of enteroendocrine cells than previously characterized driver pairs. The new pair demonstrates less brain expression, thereby providing better tools for disentangling the physiological roles of gut- and brain-secreted peptides. We also identified additional split-GAL4 drivers that promote expression in discrete subpopulations of enteroendocrine cells. Overall, the tools reported here will help researchers better target enteroendocrine cell subpopulations.
A genome-wide association and prediction study in grapevine deciphers the genetic architecture of multiple traits and identifies genes under many new QTLs
Authors: Flutre Timothée , Le Cunff Loïc , Fodor Agota , Launay Amandine , Romieu Charles , Berger Gilles , Bertrand Yves , Terrier Nancy , Beccavin Isabelle , Bouckenooghe Virginie , Roques Maryline , Pinasseau Lucie , Verbaere Arnaud , Sommerer Nicolas , Cheynier Véronique , Bacilieri Roberto , Boursiquot Jean-Michel , Lacombe Thierry , Laucou Valérie , This Patrice , Péros Jean-Pierre , Doligez Agnès
Published: April 2022

To cope with the challenges facing agriculture, speeding-up breeding programs is a worthy endeavor, especially for perennial species such as grapevine, but requires understanding the genetic architecture of target traits. To go beyond the mapping of quantitative trait loci in bi-parental crosses, we exploited a diversity panel of 279 Vitis vinifera L. cultivars planted in 5 blocks in the vineyard. This panel was phenotyped over several years for 127 traits including yield components, organic acids, aroma precursors, polyphenols, and a water stress indicator. The panel was genotyped for 63k single nucleotide polymorphisms by combining an 18K microarray and genotyping-by-sequencing. The experimental design allowed to reliably assess the genotypic values for most traits. Marker densification via genotyping-by-sequencing markedly increased the proportion of genetic variance explained by single nucleotide polymorphisms, and 2 multi-single nucleotide polymorphism models identified quantitative trait loci not found by a single nucleotide polymorphism-by-single nucleotide polymorphism model. Overall, 489 reliable quantitative trait loci were detected for 41% more response variables than by a single nucleotide polymorphism-by-single nucleotide polymorphism model with microarray-only single nucleotide polymorphisms, many new ones compared with the results from bi-parental crosses. A prediction accuracy higher than 0.42 was obtained for 50% of the response variables. Our overall approach as well as quantitative trait locus and prediction results provide insights into the genetic architecture of target traits. New candidate genes and the application into breeding are discussed.
Coexpression of MEIOTIC-TOPOISOMERASE VIB-dCas9 with guide RNAs specific to a recombination hotspot is insufficient to increase crossover frequency in Arabidopsis
Authors: Yelina Nataliya E , Holland Daniel , Gonzalez-Jorge Sabrina , Hirsz Dominique , Yang Ziyi , Henderson Ian R
Published: April 2022

During meiosis, homologous chromosomes pair and recombine, which can result in reciprocal crossovers that increase genetic diversity. Crossovers are unevenly distributed along eukaryote chromosomes and show repression in heterochromatin and the centromeres. Within the chromosome arms, crossovers are often concentrated in hotspots, which are typically in the kilobase range. The uneven distribution of crossovers along chromosomes, together with their low number per meiosis, creates a limitation during crop breeding, where recombination can be beneficial. Therefore, targeting crossovers to specific genome locations has the potential to accelerate crop improvement. In plants, meiotic crossovers are initiated by DNA double-strand breaks that are catalyzed by SPO11 complexes, which consist of 2 catalytic (SPO11-1 and SPO11-2) and 2 noncatalytic subunits (MTOPVIB). We used the model plant Arabidopsis thaliana to coexpress an MTOPVIB-dCas9 fusion protein with guide RNAs specific to the 3a crossover hotspot. We observed that this was insufficient to significantly change meiotic crossover frequency or pattern within 3a. We discuss the implications of our findings for targeting meiotic recombination within plant genomes.
Seasonal terrestrial water load modulation of seismicity at the southeastern margin of the Tibetan Plateau constrained by GNSS and GRACE data
Authors: She Yawen , Fu Guangyu , Xu Changyi
Published: April 2022

The seasonal terrestrial water load modulation of seismicity is an important phenomenon to understand the mechanism behind earthquake triggering and nucleation. The presence of high-level seismicity and large seasonal water load amplitudes at the southeastern margin of the Tibetan Plateau provides a natural experimental environment for studying the modulation mechanism. The spatiotemporal distribution of the water load was inverted using Global Navigation Satellite System (GNSS) and Gravity Recovery and Climate Experiment (GRACE) data, and an earthquake catalogue (M ≥ 2.5) was declustered to obtain the background seismicity using the Epidemic Type Aftershock Sequences (ETAS) model. The Multichannel Singular-Spectrum Analysis (M-SSA) is adopted to the time-series of monthly averaged terrestrial water load and background seismicity rates, and the results show 1- and 2-yr periodicities in the seismicity rates and water load. The 1-yr periodicity in the seismicity rate is correlated with the rate of change of the monthly averaged water load. To evaluate the seasonal principal stress perturbations on the tectonic background stress orientations, the stress changes caused by the seasonal water load changes are projected onto the tectonic background stress field orientations constraining by 8 yr of earthquake focal mechanism solutions. The results show that the largest change of the seasonal principal stress perturbations is about 16 kPa. The number of excess earthquakes is evaluated with the background seismicity rates for discrete stress intervals. The results indicate a ∼10 per cent increase in the seismicity rates that correlate with the rates of the minimum and mean principal stress perturbations. The results above can be explained by the model of harmonic stress perturbations on rate-and-state fault. Based on this model, the nucleation period of the seasonal seismicity should be less than 1 yr at the southeastern margin of the Tibetan Plateau.