Miracle-dz/UniFAR-FTUs huggingface dataset:
MG CATHODE AND ITS THERMAL EMITTANCE

A Mg cathode manufacture and operational procedure were developed at the Brookhaven National Laboratory (BNL). Mg cathde been operating routinely at a field of 100 MV/m with quantum efficiency (QE) of 0.2 to 0.3%. Good vacuum (better than 10 -9 Torr operating vacuum) and vacuum based laser cathode cleaning are critical to maintain the above QE. Experimental measurements show that, the photo-emission process in the RF gun is the Schottky dominated surface photo-emission. Emittance as functions of the RF gun phase and laser spot size were experimentally characterized for charges less than 120 pC at the beam energy of 45 MeV. The up limit of the thermal emittance deduced from our experimental data is 0.4 mm-mrad/mm, which contradict with earlier experiment and conventional theory [1-3]. The optimized emittance for a 0.5 nC charge beam is 0.6±0.2 mm-mrad.
ANALYSIS OF MINDLIN–REISSNER PLATES USING CELL-BASED SMOOTHED RADIAL POINT INTERPOLATION METHOD

In this paper, a formulation for the static and free vibration analysis of Mindlin–Reissner plates is proposed using the cell-based smoothed radial point interpolation method (CS-RPIM) with sub-domain smoothing operations. The radial basis functions augmented with polynomial basis are employed to construct the shape functions that have the Delta function property. The generalized smoothed Galerkin (GS-Galerkin) weakform is adopted to discretize the governing differential equations, and the curvature smoothing is performed to relax the continuity requirement and to improve the accuracy and the rate of convergence of the solution. The present CS-RPIM formulation is based on the first-order shear deformation plate theory, with effective treatment for shear-locking and hence is applicable to both thin and relatively thick plates. To verify the accuracy and stability of the present formulation, intensive comparison studies are conducted with existing results available in the literature and good agreements are obtained. The numerical examples confirm that the present method is shear-locking free and very stable and accurate even using extremely distributed nodes.
Accurate Positioning for Refueling Plug with Coarse-to-fine Registration and Pose Correction*

Automatic refueling robot can free people from heavy work. However, work on the pose estimation of the refueling plug is relatively sparse. To this end, a novel precise positioning method for 6-DoF (Six-Degrees of Freedom) pose of the refueling plug is introduced based on coarse-to-fine template matching and pose correction. The coarse registration matrix is constructed by extracting 3D keypoints at the edge of the point cloud and combining with the geometric characteristics of the refueling plug. On the basis of coarse registration, fine registration is performed by aligning the main direction of the refueling plug handle. Through template matching, the grab coordinate system is constructed on the handle of the refueling plug, and the pose is corrected by modifying the grab coordinate system. The developed algorithm avoids building a large template library and reduces computing requirements. In addition, the accuracy and robustness of the 6-DoF pose estimation are proved on the automatic refueling robot.
Measurement of scatter broadening for 27 pulsars at 327 MHz

New measurements of scattering delay for 27 pulsars at 327 MHz are presented. These measurements significantly improve on the available set of measurements for pulsars with dispersion measures in the range 100 to 250 pc cm-3• These measurements also sample an important section of the Galactic volume which should render better modelling of the electron density distribution. The dependence of the scatter broadening on the dispersion measure is discussed, and modelled based on the new data combined with similar, earlier, measurements.
Near-infrared photonic band gaps and nonlinear effects in negative magnetic metamaterials

We describe and characterize a nanostructured metallic photonic crystal metamaterial which is magnetically active in the near-infrared region of the spectrum. The periodic array of modified split-ring resonator structures is numerically demonstrated to have a negative effective permeability at telecommunications wavelengths. Local electric fields in the structure can be many orders of magnitude larger than in free space thus allowing for enhanced nonlinear effects. We have derived an expression for the change in the resonance frequency of the structure due to the Kerr nonlinear index change and estimate a characteristic magnetic field strength for the observation of bistable behavior.
Electric Power Carbon Emission Prediction based on Stacking Ensemble Model with K-fold Cross Validation

With the increasing global awareness of climate change, countries and regions worldwide have made ambitious plans, regulations and supports, for the carbon-neural aspirations. For China, decarbonizing its power sector, which accounts for 40% of the total emission, is particularly important to reach its carbon-neutral objective. Research shows that an accurate projection of electricity consumption, if available, can significantly contribute to power management tasks, leading to better power efficiency and directly contributing to the decarbonization task for the power sector. To solve this problem, this paper proposes a novel electric power carbon emission prediction approach based on the stacking ensemble model. It constructs a stacking ensemble model with k nearest neighbor (KNN), decision tree (DT), AdaBoost and XGBoost as the base learners and gradient boosting decision tree (GBDT) as the meta learner to improve the final prediction accuracy. The experimental results show that the stacking ensemble model constructed in this paper performs better than the traditional model in terms of RMSE, MAE and R2.
Intelligent Compound Selection of Anti-cancer Drugs Based on Multi-Objective Optimization

In the compound selection process of anti-cancer drugs, safety properties such as drug activity and pharmacokinetics need to be considered simultaneously. To construct a more complete and precise drug screening mechanism, this paper proposed an intelligent compound selection method for anti-cancer drugs based on multi-objective optimization. The proposed model is executed in the MapReduce environment. Quantitatively analyze the biological activity of the compound, and qualitatively analyze the properties of pharmacokinetics and safety properties (Absorption, Distribution, Metabolism, Excretion, and Toxicity) to build a multi-objective optimization model. Guided by Pareto optimization theory, the set of non-inferior solution values was determined, and the compound combination that satisfies the optimization goal was found by genetic optimization. On this basis, a Monte Carlo hypothesis test was used to determine the equipped range of the compounds. Finally, an example of the compound selection of anti-breast cancer drugs is given, and the experimental evaluation proves that the algorithm can screen compounds limitedly, which provides a basis for anti-cancer drug synthesis.
Two‐degree‐of‐freedom controller design for linear parameter‐varying systems

A design strategy for linear parameter‐varying (LPV) systems is considered in a two‐degree‐of‐freedom (TDOF) control framework. First, a coprime factorization for LPV systems is introduced. Second, based on the coprime factorization, a TDOF control framework of linear timeinvariant systems is extended to that of LPV systems. Good tracking performance and good disturbance rejection are achieved by a feedforward controller and a feedback controller, respectively. Furthermore, each controller design problem can be formulated in terms of a linear matrix inequality related to the L2 gain performance. Finally, a simple design example is illustrated. Copyright © 2008 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society
Circular Economy and Construction Supply Chains

With increasing complexity of global construction supply chains and the substantial contribution such supply chains make to the environment, there is a need to understand how components of these supply chains can be reused and repurposed. Blockchains provide an important basis for recording transactions carried out in supply chains to aid potential reusability.A recent example of circularity in the built environment includes the tracking of material reuse across the building lifecycle (from construction to demolition and then reuse). The use of decentralisation and immutability in Blockchains is used to demonstrate how material passports may be supported and used as a basis to create a circular economy in construction.
Underwater Soft Gripper Hydraulic Drive Control System Based on Rigid-flexible Coupling Accumulator

Underwater manipulators are critical in the development of marine resources. Traditional rigid manipulators cannot be applied for underwater operations requiring non-destructive grasping, such as biological sampling and artifact salvage, due to their large size and dimensions and complex force feedback control. Soft robotics underwater manipulators overcome this challenge by providing a dexterous and lightweight arm and gripper, but still require high power drive elements and high-frequency valve control components to achieve the required dynamic performance. In this work, we propose a rigid-flexible coupling accumulator that takes into account the lightweight characteristics of the flexible accumulator and the strong energy storage characteristics of the rigid accumulator, starting from the high-power drive unit. On this basis, we propose a hydraulic drive control system based on the rigid-flexible coupling accumulator for the submerged soft gripper. The system can achieve depth self-adaptation and a fast and stable drive for different volumes of the soft gripper, facilitating the application of soft grippers in marine resource exploitation. The proposed design method and analytical model of the rigid-flexible accumulator can also be used as a guide for other applications.
Tectorigenin targets PKACα to promote GLUT4 expression in skeletal muscle and improve insulin resistance in vitro and in vivo

The decreased expression and dysfunction of glucose transporter 4 (GLUT4), the insulin-responsive glucose transporter, are closely related to the occurrence of insulin resistance (IR). To improve the expression of GLUT4 may represent a promising strategy to prevent and treat IR and type 2 diabetes (T2DM). Here, we demonstrate that the natural compound tectorigenin (TG) enhances GLUT4 expression, glucose uptake and insulin responsiveness via activating AMP-activated protein kinase (AMPK)/myocyte enhancer factor 2 (MEF2) signaling in both normal and IR skeletal muscle cells and tissues. Accordingly, prophylactic and therapeutic uses of TG can significantly ameliorate IR and hyperglycemia in T2DM mice. Mechanistically, we identify protein kinase A catalytic subunit α (PKACα) as the target of TG to increase GLUT4 expression and TG-PKACα binding promotes the dissociation of PKACα from the regulatory subunits, leading to the activation of PKA/AMPK signaling. PKACα knockdown in local quadriceps muscles almost completely abolished the therapeutic effects of TG on IR and T2DM, as well as the enhancement on AMPK signaling and GLUT4 expression in skeletal muscle. This study supports TG as a new drug candidate to treat IR and its related diseases, but also enriches our knowledge of PKA signaling in glucose metabolism in skeletal muscle.
Field Grape Berry Counting Algorithm Based on Spatial Attention Mechanism

Automated grape yield estimation is one of the important aspects of intelligent vineyard management. In order to meet requirements of fast estimation and large-scale grape yield estimation in complex field environments, this paper proposes a Spatial Attention Grape Berry Counting Network (SAGBCNet). Firstly, the Spatial Feature Network (SFNet) is used to extract more spatial information of grape berries in image. Then attention mechanism is used to adaptively fit the long-distance context features of location and channel, so as to effectively distinguish the grape berry from background. Finally, through Feature Fusion Network, feature maps of different scales are fused to generate the predicted density map, and counting results of grape berries in the field are obtained. The experiment on the field grape counting dataset showed that SAGBCNet obtained a lower counting error for grape berries. The mean absolute error (MAE) and mean squared error (MSE) were 35.39 and 47.39 respectively.
Simulation of transition and turbulence decay in the Taylor–Green vortex

Conventional large-eddy simulation (LES) and monotone integrated LES (MILES) are tested in emulating the dynamics of transition to turbulence in the Taylor–Green vortex (TGV). A variety of subgrid scale (SGS) models and high-resolution numerical methods are implemented in the framework of both incompressible and compressible fluid flow equations. Comparisons of the evolution of characteristic TGV integral measures are made with previously reported and new direct numerical simulation (DNS) data. The computations demonstrate that the convective numerical diffusion effects in the MILES methods can consistently capture the physics of flow transition and turbulence decay without resorting to an explicit SGS model, while providing accurate prediction of established theoretical findings for the kinetic energy dissipation, energy spectra, enstrophy and kinetic energy decay. All approaches tested provided fairly robust computational frameworks.
Revisiting Congestion Detection in Lossless Networks

Congestion detection is the cornerstone of end-to-end congestion control. Through in-depth observations and understandings, we reveal that existing congestion detection mechanisms in mainstream lossless networks (i.e., Converged Enhanced Ethernet and InfiniBand) are improper, due to failing to cognize the interaction between hop-by-hop flow controls and congestion detection behaviors in switches. We define the ternary states of switch ports and present Ternary Congestion Detection (TCD) for mainstream lossless networks. TCD utilizes the ON-OFF sending pattern and the feature of queue length evolutions to detect the transitions among ternary states. We also enable TCD under the practical multiple queues scenario by TCD-MQ. Testbed and extensive simulations demonstrate that TCD can detect congestion ports accurately and identify flows contributing to congestion as well as flows only affected by hop-by-hop flow controls. Meanwhile, we shed light on how to incorporate TCD with rate control. Case studies show that existing congestion control algorithms can achieve <inline-formula> <tex-math notation="LaTeX">$3.3\times $ </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">$2.0\times $ </tex-math></inline-formula> better median and 99th-percentile FCT slowdown by combining with TCD.
Simulations of magnetic reconnection from centrifugal breakout

This thesis is the first step toward the goal of modeling centrifugal breakout from massive stars while including realistic magnetic reconnection physics. We use a plasma-physics based approach to analyze the magnetic reconnection which occurs in a stellar magnetosphere during centrifugal breakout. We modify a magentohydrodynamic code and test it by simulating an Alfven wave and a Rayleigh-Taylor instabilities. The properties of the wave and the growth rate of the instability are derived in order to confirm the code’s accuracy in the benchmarking. After this, a simple model of centrifugal breakout is developed which incorporates centrifugal force, gravity, and magnetic tension. Local density sources which imitate the accumulation of mass during centrifugal breakout are found to be a viable cause of magnetic reconnection.
Integrated model simulates bigger, sweeter tomatoes under changing climate under reduced nitrogen and water input

Abstract When simulating the response of fruit growth and quality to environmental factors and cultivation practices, the interactions between the mother plant and fruit need to be considered as a whole system. Here, we developed the integrative Tomato plant and fruit Growth and Fruit Sugar metabolism (TGFS) model by coupling equations describing the biophysical processes of leaf gas exchange, water transport, carbon allocation, organ growth and fruit sugar metabolism. The model also accounts for effects of soil nitrogen and atmospheric CO2 concentration on gaseous exchange of water and carbon by the leaf. With different nitrogen and water input values, TGFS performed well at simulating the dry mass of the tomato leaf, stem, root, and fruit, and the concentrations of soluble sugar and starch in fruit. TGFS simulations showed that increasing air temperature and CO2 concentration has positive effects on fruit growth, but not on sugar concentrations. Further model-based analyses of cultivation scenarios suggest that, in the context of climate change, decreasing N by 15%–25% and decreasing irrigation by 10%–20% relative to current levels would increase tomato fresh weight by 27.8%–36.4% while increasing soluble sugar concentration by up to 10%. TGFS provides a promising tool to optimise N and water inputs for sustainable high-quality tomatoes.
Plant breeding advancements with “CRISPR-Cas” genome editing technologies will assist future food security

Genome editing techniques are being used to modify plant breeding, which might increase food production sustainably by 2050. A product made feasible by genome editing is becoming better known, because of looser regulation and widespread acceptance. The world’s population and food supply would never have increased proportionally under current farming practices. The development of plants and food production has been greatly impacted by global warming and climate change. Therefore, minimizing these effects is crucial for agricultural production that is sustainable. Crops are becoming more resilient to abiotic stress because of sophisticated agricultural practices and a better understanding of the abiotic stress response mechanism. Both conventional and molecular breeding techniques have been used to create viable crop types both processes are time-consuming. Recently, plant breeders have shown an interest in genome editing approaches for genetic manipulation that use clustered regularly interspaced short palindromic repeats (CRISPR/Cas9). To ensure the security of the food supply in the future, plant kinds with desired traits must be developed. A completely new era in plant breeding has begun because of the revolution in genome editing techniques based on the CRISPR/CRISPR-associated nuclease (Cas9) systems. All plants may effectively target a particular gene or group of loci using Cas9 and single-guide RNA (sgRNA). CRISPR/Cas9 can thereby save time and labor compared to conventional breeding methods. An easy, quick, and efficient method for directly altering the genetic sequences in cells is with the CRISPR and Cas9 systems. The CRISPR-Cas9 system, which was developed from components of the earliest known bacterial immune system, allows for targeted gene breakage and gene editing in a variety of cells/RNA sequences to guide endonuclease cleavage specificity in the CRISPR-Cas9 system. Editing can be directed to practically any genomic site by altering the guide RNA (gRNA) sequence and delivering it to a target cell along with the Cas9 endonuclease. We summarize recent CRISPR/Cas9 plant research findings, investigate potential applications in plant breeding, and make predictions about likely future breakthroughs and approaches to food security through 2050.
Impact of Inherited Foreland Relief on Retro‐Foreland Basin Architecture

We use a Landscape Evolution Model including flexural isostasy to investigate the influence of inherited foreland relief on the stratigraphic evolution of the retro‐foreland domain during mountain building. We show models with four different types of initial relief in the foreland domain: at sea level, elevated (+300 m), a 1 km‐deep and 100 km‐wide foreland basin associated with either a forebulge at sea level or elevated at +300 m. During the first 10 Myr of simulation, the landscape evolution of the foreland is significantly altered by its inherited bathymetry/topography. The impact is then smoothed out once the foreland slope has stabilized and develops a transverse drainage network. Models record a long‐term shallowing‐up mega‐sequence driven by the increase in sediment production rate in the uplifting range and the decrease in the rate of flexural accommodation space creation in the foreland basin. The initial relief of the foreland domain alters the timing of its transition from the under‐filled to the over‐filled phase. An initially deep foreland basin is twice as thick as an initially elevated foreland. It records deep marine deposits while a foreland initially at sea level records thin shallow marine and an elevated foreland records continental deposits. The forebulge is buried by continental deposits in an initially elevated foreland while it is buried by marine sediments in other models. Alluvial fans at the foot of the range are more elevated in initially elevated forelands. We discuss our results of modeled stratigraphic architecture in comparison with the Pyrenean, Alpine and Andean retro‐foreland basins.
Experimental Identification of a Fractional Derivative Linear Model for Viscoelastic Materials

Non integer, fractional order derivative rheological models are known to be very effective in describing the linear viscoelastic dynamic behaviour of mechanical structures made of polymers [1]. The application of fractional calculus to viscoelasticity can be physically consistent [2][3][4] and the resulting non integer order differential stress-strain constitutive relation provides good curve fitting properties, requires only a few parameters and leads to causal behaviour [5]. When using such models the solution of direct problems, i.e. the evaluation of time or frequency response from a known excitation can still be obtained from the equations of motion using standard tools such as modal analysis [6]. But regarding the inverse problem, i.e. the identification from measured input-output vibrations, no general technique has so far been established, since the current methods do not seem to easily work with differential operators of non integer order. In this paper a frequency domain method is proposed for the experimental identification of a linear viscoelastic model, namely the Fractional Zener also known as Fractional Standard Linear Solid [5], to compute the frequency dependent complex stress-strain relationship parameters related to the material. The procedure is first checked with respect to numerically generated frequency response functions for testing its accuracy, and then to experimental inertance data from a free-free homogeneous beam made of High Density Polyethylene (HDPE) in plane flexural and axial vibration.Copyright © 2005 by ASME
Distributed Finite-time Consensus-Based Economic Dispatch Using Event-triggered Mechanism

A distributed finite-time consensus-based economic dispatch algorithm is proposed for smart grid using event-triggered mechanism. The scheme is implemented based on a multi-agent system structure, which only depends on the local communication and computation among neighboring agents. For smart grids without generator constraints, distributed event-triggered controllers are built to achieve the finite-time consensus of the incremental cost. Then a projection operator is used for each generator to deduce the power output when its generating capacity is limited. Simulation example is given to test the effectiveness of the proposed algorithm.