Miracle-dz/UniFAR-FTUs huggingface dataset:
Incidence and Distribution of Barley yellow dwarf virus Infecting Oats in Korea

A survey of Barley yellow dwarf virus (BYDV) was conducted in major oat-growing areas of Korea in 2020. BYDV is an economically important pathogen of cereal crops that can be transmitted by aphids. The present study evaluated the genetic composition of BYDV in oat from eight geographical areas in Korea. Multiplex reverse transcription-polymerase chain reaction was used to screen 322 oat leaf samples for six BYDV strains (PAV, MAV, SGV, PAS, RPV, and RMV). The 125 samples (~39%) tested positive for BYDV. BYDV-PAV, BYDV-SGV, BYDV-PAS, and BYDV-RPV were detected from oat in different areas. Most of the BYDV-infected samples were assigned to subgroup I (n=112). The results indicate that BYDV-PAV could be dominant throughout Korea. Also, the phylogenetic analysis of coat protein sequences indicated that 23 BYDV isolates from Korea could be separated into two clades, which exhibited high nucleotide sequence similarity. In conclusion, the present survey provides a BYDV infection assessment for domestic oat varieties in Korea and basic information for the development of BYDV control measures in Korea’s oat industry.
The influence of flight height and overlap on UAV imagery over featureless surfaces and constructing formulas predicting the geometrical accuracy

ABSTRACT The improvement of unmanned aerial system and photogrammetric computer vision (CV) algorithms has presented an aerial imaging technique for high accuracy and low-cost alternatives for mapping and topographic applications. Structure from motion (SFM) is an automation photogrammetric CV algorithm used for generating 3D coloured point clouds and 3D models from overlapping images. One of the biggest problems preventing the automation extraction and matching key points in the aligning aerial images is the non-texture of the covered area surface. This paper assessed the effect of flight altitude and overlap degree on 3D point clouds’ geometric accuracy and models produced by unmanned aerial vehicle (UAV) images captured over non-textured sandy areas. Four flight altitudes (140, 160, 180 and 200 m) related to spatial resolution (3.41, 3.9, 4.39 and 4.68 cm/pix ground sample distance (GSD)), respectively, and three overlap levels (60%, 70% and 80%) were assessed using RGB images captured by UX5 UAV over a non-textured sandy area in Jahra, Kuwait. The results showed that altitude increment might reduce flight time, processing time and cost, keeping with the acceptable and suitable geometric accuracy. Generally, favourable results are obtained for the four altitudes and overlap degrees of 80% at least. Multivariate nonlinear regression analysis was used to fit the relation between geometric accuracy, image overlap and GSD cm/pixel for the seven missions determining two formulas that predict the geometrical accuracy of the UAV point cloud with a precision of 92.76% and 91.91% for both formulas.
Enhanced Magnetic Hyperthermia of Magnetoferritin through Synthesis at Elevated Temperature

Iron oxide nanoparticles have attracted a great deal of research interest in recent years for magnetic hyperthermia therapy owing to their biocompatibility and superior thermal conversion efficiency. Magnetoferritin is a type of biomimetic superparamagnetic iron oxide nanoparticle in a ferritin cage with good monodispersity, biocompatibility, and natural hydrophilicity. However, the magnetic hyperthermic efficiency of this kind of nanoparticle is limited by the small size of the mineral core as well as its low synthesis temperature. Here, we synthesized a novel magnetoferritin particle by using a recombinant ferritin from the hyperthermophilic archaeon Pyrococcus furiosus as a template with high iron atom loading of 9517 under a designated temperature of 90 °C. Compared with the magnetoferritins synthesized at 45 and 65 °C, the one synthesized at 90 °C displays a larger average magnetite and/or maghemite core size of 10.3 nm. This yields an increased saturation magnetization of up to 49.6 emu g−1 and an enhanced specific absorption rate (SAR) of 805.3 W g−1 in an alternating magnetic field of 485.7 kHz and 49 kA m−1. The maximum intrinsic loss power (ILP) value is 1.36 nHm2 kg−1. These results provide new insights into the biomimetic synthesis of magnetoferritins with enhanced hyperthermic efficiency and demonstrate the potential application of magnetoferritin in the magnetic hyperthermia of tumors.
Bovine Respiratory Disease: Conventional to Culture-Independent Approaches to Studying Antimicrobial Resistance in North America

Numerous antimicrobial resistance (AMR) surveillance studies have been conducted in North American feedlot cattle to investigate the major bacterial pathogens of the bovine respiratory disease (BRD) complex, specifically: Mannheimia haemolytica, Pasteurella multocida, Histophilus somni, and Mycoplasma bovis. While most bacterial isolates recovered from healthy cattle are susceptible to a repertoire of antimicrobials, multidrug resistance is common in isolates recovered from cattle suffering from BRD. Integrative and conjugative elements (ICE) have gained increasing notoriety in BRD-Pasteurellaceae as they appear to play a key role in the concentration and dissemination of antimicrobial resistant genes. Likewise, low macrolide susceptibility has been described in feedlot isolates of M. bovis. Horizontal gene transfer has also been implicated in the spread of AMR within mycoplasmas, and in-vitro experiments have shown that exposure to antimicrobials can generate high levels of resistance in mycoplasmas via a single conjugative event. Consequently, antimicrobial use (AMU) could be accelerating AMR horizontal transfer within all members of the bacterial BRD complex. While metagenomics has been applied to the study of AMR in the microbiota of the respiratory tract, the potential role of the respiratory tract microbiome as an AMR reservoir remains uncertain. Current and prospective molecular tools to survey and characterize AMR need to be adapted as point-of-care technologies to enhance prudent AMU in the beef industry.
Prediction-Based Resource Deployment and Task Scheduling in Edge-Cloud Collaborative Computing

Edge computing is becoming increasingly commonplace, as consumer devices become more computationally capable and network connectivity improves (e.g., due to 5G). With the rapid development of edge computing and Internet of Things (IoT), the use of edge-cloud collaborative computing to provide service-oriented network application (i.e., task) in edge-cloud IoT has become an important research topic. In this paper, we present an edge-cloud collaborative computing framework and our resource deployment algorithm with task prediction (RDAP). Based on our paradigm, tasks in the cloud service center are predicted using the two-dimensional time series, and task classification aggregation and delay threshold determination are combined to optimize task resource deployment of edge servers. A task scheduling algorithm with Pareto improvement (TSAP) is also proposed. At the edge servers, the Pareto progressive comparison is conducted in two stages to obtain the tangent point or any intersection point of the two objective curves of user’s quality of service and effect of system service to optimize task scheduling. The experimental results show that for varying user task scales and different Zipf distribution α parameters, combining RDAP and TSAP (RDAP-TSAP) can improve the average user task hit rate. In addition, the average task completion time of users, the overall system service effect, and the total task delay rate of RDAP-TSAP are better than TSAP and the benchmark algorithms for task scheduling.
The Effect of Sharia Trust and Compliance on Consumer Loyalty through Commitment and Customer Intimacy in PT Bank Aceh Sharia

This study aims to examine the effect of trust and sharia compliance on consumer loyalty through commitment and customer intimacy at PT Bank Aceh Syariah Operational Headquarters (BAS-KPO). The population is all BAS-KPO customers, totaling 300,078 customers. The sample was determined using a simple random sampling technique so that a total sample of 260 people was obtained. The measurement scale used is the Likert Summarated Rating Scale. The research model was analyzed using SEM-AMOS statistical equipment. The test results prove that trust and sharia compliance affect commitment, customer intimacy, and consumer loyalty; Trust, sharia compliance, commitment, and customer intimacy affect consumer loyalty; and commitment and customer intimacy partially mediate the effect of trust and sharia compliance on BAS-KPO consumer loyalty. This finding reveals that the model of increasing consumer loyalty in BAS-KPO is a function of increasing trust, sharia compliance, commitment, and customer intimacy. These findings prove that this research model can be the basis for the development of further research models, and for practical references, especially research subjects to review their strategies.
Differential Propagation Delay Measurement of RSFQ Library Cells Using Ring Oscillators

Performing comprehensive timing characterization of library cells and establishing their model-to-hardware correlation are essential for building robust integrated circuits and scaling circuit complexity. To measure the propagation delay of fabricated library cells, we have designed a differential delay measurement scheme using SFQ ring oscillators. The reference and design-under-test (DUT) rings are designed using circuit elements that are either common to both rings or are of nominally similar design, except for the DUT. By inserting a single pulse in the ring, the oscillation period is measured using two methods: (1) direct voltage measurement, and (2) frequency measurement using a frequency divider followed by an SFQ-to-DC converter. Subtracting delay of the two rings gives us the propagation delay of the DUT. A 1 cm by 1 cm chip and another 5 mm by 5 mm chip, incorporating stand-alone ring oscillator test structures for different library cells, have been fabricated in the MIT-LL SFQ5ee process. The chips also contain test circuits to validate two variants of the input/output multiplexing scheme that facilitate reducing the pads requirement. Two copies of a chip with fifteen DUTs were tested. The measured and simulated results for the voltage and frequency of the ring are compared. The simulations account for critical current density (Jc) and sheet resistance (Rs) fabrication parameters. In addition, we have used the Jc as a single free parameter to get a better matching with measurement results. For one of the chips, a 15% higher Jc in simulations results in better matching with measured frequency results for all the DUTs. For example, the discrepancy between simulated and measured DUT ring frequency for the NOT cell was reduced from 19% to 1% when the Jc was changed from nominal to 15% higher in simulations. Detailed measurement and simulation results for several DUTs are presented.
Towards an understanding of the structural performance of future electrified roads: a finite element simulation study

ABSTRACT Nowadays, many novel technologies are under investigations for making our road infrastructure function beyond providing mobility and embrace other features that can promote the sustainability development of road transport sector. These new roads are often referred to as multifunctional or ‘smart’ roads. Focus in this paper is given to the structural aspects of a particular smart road solution called electrified road or ‘eRoad’, which is based on enabling the inductive power transfer technology to charge electric vehicles dynamically. Specifically, a new mechanistic-based methodology is firstly presented, using a finite element simulation and an advanced constitutive model for the asphalt concrete materials. Based on this, the mechanical responses of a potential eRoad structure under typical traffic loading conditions are predicted and analysed thoroughly. The main contributions of this paper include thus: (1) introducing a new methodology for analysing a pavement structure purely based on mechanistic principles; (2) utilising this methodology for the investigation of a future multifunctional road pavement structure, such as an eRoad; and (3) providing some practical guidance for an eRoad pavement design and the implementation into practice.
A TV demonstration of sound absorption connecting the space shuttle to submarines

In 2009 we were invited to provide an item for the BBC TV program ‘Engineering Connections with Richard Hammond’, to be broadcast in 2011. Each episode in the series considers a single engineering masterpiece, and examines the host of previous engineering innovations which provided the necessary background for (or nicely illustrate in hindsight) the engineering solutions employed to make the masterpiece work. The enquiry was for a program about the space shuttle. The production team (Darlow Smithson Productions) had heard that acoustic energy generated at launch could, without mitigation, be damaging to the protective tiles on the shuttle, or to instrumentation in, or carried by, the shuttle. We were asked to provide a demonstration on this acoustical aspect of the shuttle (Fig. 1). Following the filming, it was suggested that the technical aspects of the build be written up for a special ‘Education in Acoustics’ issue of the Journal of the Acoustical Society of America, and readers are advised to consult that paper for those details. However the current article was suggested to explain the applications of the acoustics contained in that demonstration, those applications being the focus of the TV show. A secondary aim of this article is to describe the process of getting the demonstration to work for the TV show, outlining the constraints and solutions for those wishing to undertake such jobs in future. The over-riding factor was that, rather than come to film us, the TV company required that we take the demonstration to them as just one item in a packed day of filming. Hence the apparatus would have to be transportable, constructed quickly on site and work first time. This resembles the field work that many practicing acoustic consultants undertake (as opposed to the laboratory experiments of a controlled academic environment), although without the benefit of familiar commercial equipment or prior experience. Because we were a small component of the show, the date depended on the availability of the presenter and others, and so the actual filming date was set at short notice. The budget was small, and covered not much more than the hire of the Ford Galaxy we eventually used to transport the demonstration. Therefore the apparatus had to be constructed from items we already had to hand. A series of telephone conversions with the program’s researcher, Rachel Millar, established that an appropriate narrative (with practical demonstration) was feasible. That narrative had to link the sound suppression system at the shuttle launch with what could feasibly be built from our current apparatus, maintaining the priority that the story, facts and explanations had to be scientifically rigorous and factually correct. Furthermore, the narrative had to be compelling and understandable to an audience of young viewers, whilst of course remaining entirely honest in the extent of the link between the technologies and the explanations of how the science works.
A SLAM System with Direct Velocity Estimation for Mechanical and Solid-State LiDARs

Simultaneous localization and mapping (SLAM) is essential for intelligent robots operating in unknown environments. However, existing algorithms are typically developed for specific types of solid-state LiDARs, leading to weak feature representation abilities for new sensors. Moreover, LiDAR-based SLAM methods are limited by distortions caused by LiDAR ego motion. To address the above issues, this paper presents a versatile and velocity-aware LiDAR-based odometry and mapping (VLOM) system. A spherical projection-based feature extraction module is utilized to process the raw point cloud generated by various LiDARs, hence avoiding the time-consuming adaptation of various irregular scan patterns. The extracted features are grouped into higher-level clusters to filter out smaller objects and reduce false matching during feature association. Furthermore, bundle adjustment is adopted to jointly estimate the poses and velocities for multiple scans, effectively improving the velocity estimation accuracy and compensating for point cloud distortions. Experiments on publicly available datasets demonstrate the superiority of VLOM over other state-of-the-art LiDAR-based SLAM systems in terms of accuracy and robustness. Additionally, the satisfactory performance of VLOM on RS-LiDAR-M1, a newly released solid-state LiDAR, shows its applicability to a wide range of LiDARs.
Hyperspectral Image Reconstruction Based on Reference Point Nondominated Sorting Genetic Algorithm

Spatial and spectral features of hyperspectral imagery reconstruction have gained increasing attention in the latest years. Based on the study of orthogonal matching pursuit (OMP) idea, a hyperspectral image reconstruction algorithm based on reference point nondominated sorting genetic algorithm (NSGA) is proposed. Instead of directly reconstructing the entire hyperspectral data as a traditional OMP reconstruction algorithm, the proposed algorithm explores the idea of the evolution process in the reconstruction. The Gabor redundancy dictionary is established as the sparse basis of hyperspectral images, and the reconstruction model of multiobjective optimization is constructed. In the reconstruction process, the NSGA-III algorithm is used to find the optimal atoms to represent the original signal, and Hermitian inversion lemma is also used to realize the recursive update of the residuals. The initial solution generation, the definition of reference points, the association and niche-preservation operation, and the crossover and mutation operation in NSGA-III are presented in detail. Experimental results on hyperspectral data demonstrate that the proposed algorithm could maintain the reconstruction accuracy, as well as the computational efficiency, and are superior to the state-of-the-art reconstruction algorithms. The proposed algorithm could be applied in the classification and unmixing in hyperspectral images.
Pyramid dilated convolutional neural network for image denoising

Abstract. Convolutional neural network has been successfully applied to image denoising. In particular, dilated convolution, which expands the network’s receptive field, has been widely used and has achieved good results in image denoising. Losing some image information, a standard network cannot effectively reconstruct tiny image details from noisy images. To solve this problem, we propose a pyramid dilated CNN, which mainly has three pyramid dilated convolutional blocks (PDCBs) and a gated fusion unit (GFU). PDCB uses dilated convolution to expand the network’s receptive field and the pyramid structure to obtain more image details. GFU fuses and enhances the feature maps from different blocks. Experiments demonstrate that the proposed method outperforms the comparative state-of-the-art denoising methods for gray and color images. In addition, the proposed method can effectively deal with real-world noisy images.
基于NARX模型的光伏并网逆变器非线性模型辨识方法 A Nonlinear Model Identification Method of Photovoltaic Grid-Connected Inverters Based on the NARX Model

论文提出了单相光伏并网逆变器NARX模型的系统辨识方法。 针对商用光伏并网逆变器的“黑箱”特征，以及现有的线性化建模方法无法解决逆变器的强非线性问题，将单相光伏并网逆变器视为“黑箱”，无需逆变器内部电路、功率开关器件等拓扑结构和参数及其控制系统的类型和逻辑关系，仅仅利用逆变器输入–输出两侧的外部测量数据，基于NARX模型非线性系统辨识技术，可建立较为准确的数学模型，实现对商用光伏并网逆变器准确描述其动态特性的可能。 辨识所得单相光伏并网逆变器NARX模型结构简单，运算量小，在模型的复杂性和模型的精确性方面取了很好的平衡，适用于电力系统对并网光伏发电系统的调度、联合运行与协调控制、随机模拟等需要快速建模与简单模型结构的研究领域。 The system identification method of single-phase photovoltaic grid-connected inverter NARX model was proposed. For the black box feature of commercial photovoltaic grid-tied inverters, as well as the strongly nonlinear problem of the inverter which cannot be solved by existing linear modeling approach, in this method, the inverter was considered as a black box, wherein it was not necessary to know the topology and the parameters of the inverter internal circuits and power switching devices, as well as the type and logical relations of the control system. It only used the input-output external measurement data of the inverter, based on the NARX model nonlinear system identification techniques, to create an accurate mathematical model. The model can accurately imitate the behavior of the commercial inverter, and has simple structure and a small amount of computation. It takes a good balance between the complexity of the model and the model accuracy. It is suitable for power system with the grid-connected photovoltaic system scheduling, joint operation and coordinated control, and stochastic simulation research areas, in which the fast modeling and simple model structure are required.
Synthesis of high performance PM motors with concentrated windings

Windings concentrated around the teeth offer obvious advantages for electric machines with radial air-gaps, because the volume of copper used in the end-windings can be reduced. The Joule losses are decreased and the efficiency is improved. These machines are still limited to applications of sub-fractional power and they generally present a reduced number of phases. In three-phase machines, the concentrated winding is too often restricted to a winding with a short pitch of 120 electric degrees, i.e. to a winding with performances reduced compared to the traditional structures. But there are a significant number of three-phase structures which can support a concentrated winding if the number of poles is increased. In this article, the author present a synthesis of the structures of three-phase machines with concentrated windings. In the first part, the structures with a regular distribution of the slots are presented. A systematic method is proposed to determine the windings and the performances are discussed. In the second part, the authors present original structures of three-phase machines with concentrated windings which use an irregular distribution of the slots. A specific method to identify these structures is described and a comparative analysis of the performances of the original and traditional structures is performed by using field calculation software.
Robust Adaptive Joint Tracking of GNSS Signal Code Phases in Urban Canyons

Despite rapid developments in global navigation satellite system (GNSS), positioning in urban canyons is a big challenge for civil receivers. Low accessibility to the sky, multipath, weak signal and blocking incidents are the major problems of positioning in these environments. This study proposes a robust adaptive joint tracking architecture to improve the tracking and positioning results of the receiver. In this architecture beside the conventional tracking architecture, one adaptive tracking method works to aid the computation of the code phase error in weak channels. To increase the availability of the satellites above the receiver, global positioning system and Russian GLobal NAvigation satellite system integration is utilised. Different tests in static mode including blocking, multipath and weak-signal scenarios and a dynamic test in an urban environment are included. Experimental results show that the joint adaptive receiver could find the position with more than 31 and 14% improvements in RMS error rather than conventional receiver during the static multipath and dynamic tests, respectively. How the proposed method solves the fault propagation problem of vector tracking is also shown using a simulated scenario.