Miracle-dz/UniFAR-FTUs huggingface dataset:
Towards a fusion power plant: integration of physics and technology

A fusion power plant can only exist with physics and technology acting in synchrony, over space (angstroms to tens of metres) and time (femtoseconds to decades). Recent experience with the European DEMO programme has shown how important it is to start integration early, yet go deep enough to uncover the integration impact, favourable and unfavourable, of the detailed physical and technological characteristics. There are some initially surprising interactions, for example, the fusion power density links the properties of materials in the components to the approaches to waste and remote maintenance in the context of a rigorous safety and environment regime. In this brief tour of a power plant based on a tokamak we outline the major interfaces between plasma physics and technology and engineering considering examples from the European DEMO (exhaust power handling, tritium management and plasma scenarios) with an eye on other concepts. We see how attempting integrated solutions can lead to discoveries and ways to ease interfaces despite the deep coupling of the many aspects of a tokamak plant. A power plant’s plasma, materials and components will be in new parameter spaces with new mechanisms and combinations; the design will therefore be based to a significant extent on sophisticated physics and engineering models making substantial extrapolations. There are however gaps in understanding as well as data—together these are termed ‘uncertainties’. Early integration in depth therefore represents a conceptual, intellectual and practical challenge, a challenge sharpened by the time pressure imposed by the global need for low carbon energy supplies such as fusion. There is an opportunity (and need) to use emerging transformational advances in computational algorithms and hardware to integrate and advance, despite the ‘uncertainties’ and limited experimental data. We use examples to explore how an integrated approach has the potential to lead to consistent designs that could also be resilient to the residual uncertainties. The paper may stimulate some new thinking as fusion moves to the design of complete power plants alongside an evolving and maturing research programme.
Magnet Corrector Power Supply Controller for LCLS-I

The MCOR 12 is a 16-channel modular architecture, precision magnet driver, capable of providing bipolar output currents in the range from –12A to +12A. A single, unregulated bulk power supply provides the main DC power for the entire crate. Currently the MCORs have a 1000ppm regulation on the B-field. The MCOR controller card upgrades, existing LCLS-I and future LCLS-II needed, controls for Magnet Corrector Power Supplies. The project shifts the existing functionality of the VME based DAC and SAM and an Allen Bradley PLC into a new slot-0 card residing in the MCOR chassis. Elimination of the VME crate and the PLC will free up rack space to be used in future. The new interface card has a long term stability of 100ppm and monitors ground fault currents and various other interlocks for the MCOR power supplies. The controller can interface to EPICS Channel Access and Fast Feedback system at SLAC using two Gigabit Ethernet ports and has an FPGA based EVR for getting “time stamps” from the Event Generator system at SLAC. The EPICS control system along with embedded diagnostic features will allow for enhanced remote control and monitoring of the power supplies.
Assessment of the WRF Model as a Guidance Tool Into Cloud Seeding Operations in the United Arab Emirates

With the projected expansion of arid/semi‐arid regions in a warming world, precipitation enhancement activities such as cloud seeding will become increasingly popular and relied upon. Due to the inherent costs, a successful planning is crucial, which involves accurate model predictions. In this study, the usefulness of the Weather Research and Forecasting (WRF) model forecasts for guidance into seeding operations in the United Arab Emirates, where seeding activities have been conducted for more than two decades, is assessed. The WRF predictions are compared with ground‐based, satellite‐derived and radar reflectivity data, and in‐situ observations onboard the airplanes used to perform the seeding operations. WRF is found to have higher skill in simulating the observed cloud top pressure/temperature than the cloud fraction, with the model vertical velocity predictions also more skillful than those of the radar reflectivity. A stronger Arabian Heat Low (AHL) in the model leads to drier conditions which, together with a surface cold bias, limits the spatial extent and vertical depth of the simulated convective clouds. Development of convective rolls in the boundary layer is reported in both observations and simulations and their interaction with cold pools from convective clouds promote the development of secondary convection. Sensitivity to the choice of the Planetary Boundary Layer (PBL) scheme is also noticed, with the Yonsei University PBL scheme giving the best performance. When considering the two factors needed for a successful seeding operation that is, the presence of an updraft and clouds, the model‐predicted seeding regions largely match the areas where precipitation was observed. As the proposed WRF set up can be used operationally, the model forecasts will bring added value to the seeding activities in the country.
Cooperative Robust Video Multicast in Integrated Terrestrial-Satellite Networks

Integrated terrestrial-satellite networks (ITSNs) are the promising trends of future networks. However, there exist great challenges when performing video multicast in ITSNs due to the strong heterogeneity of users in comprehensive satellite coverage and the inter-system complex co-channel interference. To overcome these, we make the first attempt to propose an efficient cooperative robust video multicast (CRVM-ITSN) framework in ITSNs. The basic idea is to leverage the non-orthogonal multiple access technique in the cooperative transmission of ITSNs to achieve high-efficiency robust video multicast. The desired robust multicast performance realizes that the recovered video quality can adapt to diverse channel conditions of users. In CRVM-ITSN, to achieve the optimal cooperative transmission performance, power allocation and chunk scheduling of video data are jointly formulated as a distortion minimization problem, which is a non-convex mixed integer non-linear programming problem. To solve it, we design a provably convergent optimal algorithm by converting it to be convex. Besides, based on the theorem on optimal chunks selection of satellite cooperative transmission, a low-complexity chunk grouping algorithm is proposed to accelerate the optimal algorithm. Simulation results have demonstrated the superiority of proposed CRVM-ITSN against existing reference schemes, achieving about 4.1dB more gains in the recovered video quality.
Metric Learning for Robust Gait Phase Recognition for a Lower Limb Exoskeleton Robot Based on sEMG

This study aims to develop a robust myoelectric control method for gait phase recognition in a lower-limb exoskeleton robot. In the proposed method, a metric learning-based temporal convolution network (ML-TCN) was utilized to extract discriminative features of the surface electromyography (sEMG) signals and recognize four gait phases: heel strike (HS), foot flat (FF), heel off (HO), and swing (SW). Vicon validated the effectiveness of the sEMG data-acquisition system. The proposed method acquires significantly more discriminative features than long short-term memory (LSTM) or common temporal convolutional network (TCN). The experimental results show that the proposed model has a higher prediction accuracy and stronger robustness against disturbances in complex terrain. Finally, under the complex terrain of level ground-ramp ascending-ramp descending walking, the proposed model’s accuracy of gait phase recognition is 96.22%, which is better than LSTM’s 91.20%. Noise disturbances of 10%, 20%, 30%, 40%, and 50% were added to the test set. Compared with LSTM, the resistance to disturbances of the proposed method increased by 8.15%, 8.79%, 9.67%, 10.6%, and 10.61%, respectively.
Incremental Compression for Image Database

Image databases obtain the incremental images frequently. However in tradition it is directly compressed to the incremental image, which ignores the redundancy and similarity between images. The general compression way is not satisfied. With an increasing number of compression method proposed, we proposed a method called incremental image compressing method aiming to this question, which is to make the best of the redundancy and similarity between image database and incremental image. Firstly, we tried to classify the incremental image, then seek the most similar image in the class as the reference image, and encode the incremental image using the redundancy and similarity. Simulations test shows the compression results are obviously improved, so the proposed method is superior to traditional compression methods.
Development of an Anthropomorphic and Dexterous Dual-Arm System for Aerial Cooperative Bimanual Manipulation

It is a challenging task for an aerial manipulator to complete dual-arm cooperative manipulation in an outdoor environment. In this study, a new dual-arm aerial manipulator system with flexible operation is developed. The dual-arm manipulator system is designed for the application of aerial manipulation, and it has the characteristics of low weight, low inertia, and a humanoid arm structure. The arm structure is composed of customized aluminum parts, each manipulator contains four degrees of freedom, similar to the arrangement of human joints, including shoulder yaw, shoulder pitch, elbow pitch, and wrist roll. Next, the workspace of the dual-arm manipulator is simulated and analyzed, and the relevant kinematic and dynamic models are deduced. Finally, through the lift load, accuracy and repeatability, cooperative bimanual manipulation tests on the test bench, and multiple groups of outdoor flight tests, the relevant performance analysis and verification of the dual-arm aerial manipulator system are carried out. The test results evaluate the feasibility of the designed dual-arm aerial manipulator system for outdoor cooperative manipulation.
A neural network architecture for automatic extraction of oceanographic features in satellite remote sensing imagery

The authors discuss an approach for automatic feature detection and sensor fusion in remote sensing imagery using a combination of neural network architecture and Dempster-Shafer theory of evidence. Deterministic or idealized shapes are used to characterize surface signatures of oceanic and atmospherically fronts manifested in satellite remote sensing imagery. Raw satellite images are processed through a bank of radial basis function (RBF) neural networks trained on idealized shapes. The final classification results from the fusion of the outputs of the separate RBF. The fusion mechanism is based on Dempster-Shafer (DS) evidential reasoning theory. The approach is initially tested for detecting different features on a single sensor, and then is extended to classifying features observed in multiple sensors.
Learning Nonlinear Feature Mapping via Constrained Non-convex Optimization for Unsupervised Salient Object Detection

Mimicking the biological visual attention mechanism to detect salient objects in images has been widely studied in recent years. Most of the existing computational models rely on external learning for saliency prediction, which however lack robustness in diversified scenes. In this paper, an unsupervised learning model is proposed to detect salient objects by fully exploiting the internal information of the scene. Specifically, we formulate saliency detection as a mathematical programming problem with which to learn a nonlinear feature mapping from multi-view features to saliency scores. The optimization objective is to maximize the between-class variance of the attended and background regions in the resulting saliency maps, which is statistically optimal. Moreover, to solve the non-convex constrained mathematical programming problem, a hybrid external point method based particle swarm optimization algorithm is developed to find the optimal solution in a rapid manner. Finally, extensive experiments are conducted on four classical saliency benchmark datasets to test the effectiveness of the proposed method and it shows superior qualitative and quantitative performance than the other 16 state-of-the-art unsupervised saliency models.
A Wideband Circularly Polarized Antenna with Wilkinson Feed Network for Worldwide UHF Band RFID Reader

A radio frequency identiflcation (RFID) reader antenna with circular polarization (CP) radiation is proposed to operate at worldwide UHF band which covers 840{960MHz. The size of the antenna is 0:555‚0 £ 0:553‚0 £ 0:099‚0. A micro-strip patch with truncated corners as the main radiation patch is placed between the wilkinson feed network layer and the parasitic patch layer. The ground plate is placed on the top of the feed network layer. The feed network is connected with the main radiation patch via two metal cylindrical probes which produce two orthogonal signals of equal amplitude and 90 degree phase difierence. The proposed antenna has wideband circularly-polarization characteristics. The truncated corners on the main radiation patch can increase 3dB axial ratio (AR) bandwidth while improving the best axial ratio. And the parasitic patch can adjust the radiation direction of the antenna while increasing its gain. The simulation results show that the proposed circularly polarized UHF reader antenna has an input impedance matching bandwidth (S11 • i10dB) of 456MHz (675{1131MHz), the band of re∞ection coe-cient S11 • i20dB covering 842{955MHz, 3-dB axial ratio bandwidth of 296MHz (741{1037MHz), minimum axis ratio reaching 0.33dB, and the highest gain reaching 3.53dBi in the operating frequency band. Both the impedance bandwidth and the axial ratio band cover the entire UHF band of RFID systems.
PowerCell Payload on Eu:CROPIS - Measuring Synthetic Biology in Space

NASA’s PowerCell payload on the DLR Eu:CROPIS satellite will compare the effect of multiple simulated gravity regimes on basic processes required for synthetic biology in space including growth, protein production, and genetic transformation of the bacterium Bacillus subtilis. In addition, it will pioneer the use of a cyanobacterially-produced https://ntrs.nasa. gov/search.jsp? R=20190000375 2020-04-16T07:21:57+00:00Z
Cross-Sectional Study on Assessment of Frequency of Intestinal Helminth Infections and Its Related Risk Factors among School Children from Adola Town, Ethiopia

The three main intestinal helminth infections (IHIs), ascariasis, trichuriasis, and hookworm, are common clinical disorders worldwide. These IHIs are more prevalent in tropics and subtropical countries especially in developing countries like sub-Saharan Africa responsible for morbidity, mortality, and physical as well as intellectual growth retardation in children. In Ethiopia, the burden of IHIs appears in all ages mainly due to factors like lack of education, low socio-economic status, and inadequate supply of drugs and proper awareness. The present study was carried out to access the prevalence of intestinal helminth infections and associated risk factors among school children in Adola town from Guji Zone, Oromia, Ethiopia, from August 2019 to December 2019. 404 stool samples were collected in a clean, dry, screw-capped, and wide-mouthed plastic container, fixed with 10% formal-saline solution, and transported to the Adola Hospital laboratory for further microscopic analysis by wet mount following formal ether concentration technique. Data were analyzed using SPSS version 20 by binary logistic regression model using odd ratio with 95% CI. The overall prevalence of IHIs among school children was found to be 33.91% (137/404). Rate of double infection was noted to be 2.72% (11/404). Most dominant species was Ascaris lumbricoides (8.9%) followed by Hymenolepis nana (7.7%), Taenia saginata (5.4%), hookworm (4.7%), Trichuris trichiura (2.5%), Schistosoma mansoni (2.2%), Enterobius vermicularis (1.7%), and Strongyloides stercoralis (0.7%), respectively. Highest prevalence was observed in male students (39.6%) compared to female students (28.8%) (P < 0.05). The prevalence of IHIs among school children in the age group of 6-10, 11-15, 16-20, and above 20 was 49.6%, 35.8%, 10.9%, and 3.6%, respectively (P < 0.05). IHI was significantly associated with some of the risk factors such as gender, educational level of students', toilet usage habit, habit of hand washing, hand washing habit before feeding and after defecation, purpose of hand washing, and awareness to intestinal helminths (P < 0.05). In the study area, the prevalence of IHIs is moderately high and represents a public health problem in the school children. Therefore, all stakeholders should pay attention to raise awareness about health education programs such as proper personal hygiene, environmental sanitation, improving the quality of drinking water, and treatment to reduce the consequences of intestinal helminths.
Diagnosis of Pulmonary Nodules on CT Images Using YOLOv4

In this paper, the Scale-Invariant Feature Transform (SIFT) and Fast Library for Approximate Nearest Neighbors (FLANN) based algorithm is used to detect the abnormalities in the National Lung Screening Trial (NLST) CT scans as the exact clinical nodule locations are not provided in the dataset. These identified nodules on NLST CT Scans are then annotated using LabelImg tool. This process consumes time and so furthermore, the automatic nodule detection, You Only Look Once version 4 (YOLOv4) object detection model is implemented. The YOLOv4 object detection model is provided with total of 4187 labelled images in form of training (70%), validation (20%), and test (10%) datasets. Our YOLOv4 model achieves precision of 95%, sensitivity of 81% and mean Average Precision (mAP) of 89.1%.
IGDT-based robust optimal utilisation of wind power generation using coordinated flexibility resources

This study investigates the application of a robust method to solve the problem of security constrained unit commitment (SCUC) with flexible resources for managing the uncertainty of significant wind power generation (WPG) to sustain the load-generation balance. The flexible resources include up/down ramping capability of thermal units, hourly demand response, energy storage system and transmission switching action through an integrated scheme. The application of mixed-integer linear programming to deal with the SCUC problem with flexibility resources has been discussed in this study using information-gap decision theory (IGDT) to realise a robust strategy for power system decision maker. Besides, this study proposes an effective solution strategy based on Benders' decomposition to solve the proposed problem. Numerical simulation results on the modified six-bus system and IEEE 118-bus system clearly demonstrate the benefits of applying flexibility resources for managing the WPG uncertainty and validate the applicability of the proposed IGDT-based SCUC model.
Numerical Analysis On Primary Conversion Efficiency of Floating OWC-type Wave Energy Converter

In order to design a floating OWC-type wave energy converter such as Backward Bent Duct Buoy (BBDB), it is necessary to develop a numerical method to make clear an optimal hull shape which maximizes the generating electrical energy. In this paper, a two-dimensional numerical method to estimate the primary conversion efficiency of a floating OWC-type wave energy converter with arbitrary cross section in frequency domain is proposed. The fluid force by water waves is calculated by using boundary element method based on velocity potential theory. For the air flow in air chamber, an equation of state and the conservation of mass and energy with the assumption of air being the perfect gas are used. From these equations for the air flow, boundary integral equation for the velocity potential and equations of motion of the floating body, motions of floating body, air pressure in air chamber, the transmission coefficient and reflection coefficient of water waves and primary conversion efficiency etc. are calculated. Wave tank tests for the primary conversion efficiency of BBDB in regular waves are also carried out and numerical results are compared with experimental results.
Towards the Simulation of Deformable Sloshing Tanks with Spline-Based Solution Methods

The structural design of liquid storage tanks is sufficient for conventional load cases. Nevertheless, extraordinary loads like seismic excitations and in combination with minor material defects can lead to a complete failure of the structure [1]. The challenges of numerical simulation of seismic effects on sloshing fluids in flexible tanks can be summarized as follows: An accurate consideration of the interaction between fluid and surface of the structure is essential; on the structural side, the numerical representation of curved shell structured has to be geometrically exact; and finally, a suitable consideration of the free-surface flow is needed, including its influence on load changes on the structure. For the solution of the surface-coupled problem in the presented work a staggered approach is applied, successively calling the single-field solvers XNS and FEAFA. The in-house code XNS is a finite element code based on the Deforming Spatial Domain/Stabilized Space-Time (DSD/SST) [2] procedure, taking the unsteady character of the problem as well as the deformable computational domain resulting from the free-surface motion and the deforming structure into account. The inhouse finite element code FEAFA solves the elastodynamic problem. Expecting minor and homogeneous surface motion, an approach following the idea of Interface-Tracking is applied to compute the free-surface flow [3]. The Elastic Mesh Update Method transfers the resulting surface displacements of both structural deformation and free-surface motion to the CFD grid. The stability analysis of tank structures is extremely sensitive to the geometrical approximation, especially if shell elements are used. To counteract this sensitivity, spline-based methods such as the isogeometric analysis can be used [4]. Following this strategy, spline-based methods are integrated into the existing partitioned approach to reduce inaccuracies in the overall analysis. The extensions include modifications not only in the solution strategies for structural and fluid mechanics as well as the free-surface problem, but also in the projection routines. Current developments and results are presented.