Miracle-dz/UniFAR-FTUs huggingface dataset:
Ionization potentials and Lamb shifts of the ground states of 4He and 3He

In order to obtain an experimental value for the Lamb shift of the ground state of helium it is necessary to determine a very precise value for the ionization potential. For this purpose the wavelengths of the far ultra-violet lines 584·3 (11S-21P), 537·0 (11S-31P) and 591·4 Å (11S-23P1) of 4He have been redetermined with much improved accuracy and those of 3He have been measured for the first time. The standards used were lines of C+ and A+ in the region 610 to 520 Å which were derived by means of the combination principle from lines at longer wavelengths. The final results for the wavelengths of the 4He lines are 584·3339, 537·0293 and 591·4121 Å with an estimated accuracy of ± 0·0005 Å. For 3He the corresponding figures, obtained by adding the measured shifts to the 4He wavelengths, are 584·3640, 537·0577 and 591·4466 Å. The term values of the upper states of these lines relative to the ionization limit have been redetermined by a new measurement of the Bergman series 33D–n3F, of the intercombination lines 23P–31D and 21P–33D and a remeasurement of the near ultra-violet 21P–n1D and 23P–n3D series. Combining these results with those of the far ultra-violet lines the following values for the ionization potentials of 4He and 3He are obtained: I. P. (4He) = 198310·82 ± 0·15 cm-1, I. P. (3He) = 198300·32 ± 0·15 cm-1. The isotope shift of the ground state, 10·50 ± 0·05 cm-1, agrees closely with the theoretical prediction. Experimental values for the Lamb shift are obtained by comparing the observed ionization potentials with those obtained from the Dirac theory not including quantum electro-dynamic effects. Using Kinoshita’s 39-parameter value, one finds a Lamb shift of —0·79 and —0·82 ± 0·15 cm-1 for 4He and 3He, respectively. [Added in proof: Using Pekeris’s 203-parameter value one finds —1·19 and —1·23 cm-1, respectively. ] The value predicted by Kabir, Salpeter & Sucher is —1·33 ± 0·2 cm-1.
PATH PLANNING ALGORITHM, BASED ON USER-DEFINED MAXIMAL LOCALIZATION ERROR

A model-based path planning algorithm will be presented in this paper. The whole model, like the algorithm, is divided into 2 parts. The 1st part begins with a map-building process over an unknown environment, which is based on the construction of the so-called Potential Field (PF) of the environment. In this part, the above mentioned PF will be created by three autonomous robots, equipped with US sensors, which will cooperate and update the global potential map on the remote host. The 2nd part begins with the calculation of the environment´s 2D mathematical model. The calculation is realized through the ythresholding of the global potential map. Furthermore, a landmark arrangement will be defined on this model. The yArtificial Error Field (AEF), which covers the entire workspace, will be calculated and the result will depend on the sensory system of the mobile robot/robots and on the landmark arrangement. Actually, the three-dimensional yAEF contains the ylocalization errors corresponding to each ` x , y ´ position of the work space´s free space. In respect of the yuser-defined maximal localization error ( v \max ), some ynavigation paths (NP) can be generated. These paths serve as the base for the calculation of the possible routes in form of directed and yweighted graph-map . The route with yminimal complexity between the start and the ydocking positions on this graph-map will be selected. Each point of the mobile robot´s exact trajectory must fit in the selected navigation path (NP). This maintains the allowed position error below the defined limit. The shape of the trajectory is calculated by the use of cubic B -splines.
Supervisory control of families of linear set-point controllers Part I. Exact matching

This paper describes a simple "high-level" controller called a "supervisor" which is capable of switching into feedback with a SISO process, a sequence of linear positioning or set-point controllers from a family of candidate controllers so as to cause the output of the process to approach and track a constant reference input. The process is assumed to be modeled by a SISO linear system whose transfer function is in the union of a number of subclasses, each subclass being small enough so that one of the candidate controllers would solve the positioning problem if the transfer function of the process were to be one of the subclasses' members. Each subclass contains a "nominal process model transfer function" about which the subclass is centred. It is shown that in the absence of unmodeled process dynamics, the proposed supervisor can successfully perform its function even if process disturbances are present, provided they are bounded and constant.
Introduction of a modified segregated numerical approach for efficient simulation of γ- transition model

An implicit approach is modified and extended for numerical simulation of four-coupled transport equations in the γ- transition model. The method preserves the positivity of all turbulence and transition variables throughout the solution convergence. While a range of segregated and coupled treatments are investigated, a modified segregated approach is shown to perform best. The developed numerical procedure is very robust and displays excellent convergence properties, two characteristics which have not been previously well reported in the literature. The approach is thoroughly verified for a range of two-dimensional transitional flow benchmarks, for which good agreement is observed in comparison with previous numerical and experimental data. Machine-level convergence is achieved for all of the simulated test cases.
Modeling bilayer polymer/fullerene photovoltaic devices

The electrical transport and charge generation of polymer/fullerene photovoltaic devices were investigated. The polymer/fullerene photodiodes were formed by a heterojunction of fullerene and a semiconducting polymer poly (3,4-ethylenedioxythiophene). The current-voltage characteristic of the devices were measured with variable thickness of the C60 layer, under monochromatic light of different wavelengths. The results show that the values of the electrical photoconductivity are related to the optical absorption coefficient of the fullerene, and thus implying a large contribution of the C60 films to the diode photocurrent.
PROJECTIVE DESCRIPTION OF WEIGHTED (LF)-SPACES OF HOLOMORPHIC FUNCTIONS ON THE DISC

Abstract The topology of certain weighted inductive limits of Fréchet spaces of holomorphic functions on the unit disc can be described by means of weighted sup-seminorms in case the weights are radial and satisfy certain natural assumptions due to Lusky; in the sense of Shields and Williams the weights have to be normal. It turns out that no assumption on the (double) sequence of normal weights is necessary for the topological projective description in the case of o-growth conditions. For O-growth conditions, we give a necessary and sufficient condition (in terms of associated weights) for projective description in the case of (LB)-spaces and normal weights. This last result is related to a theorem of Mattila, Saksman and Taskinen. AMS 2000 Mathematics subject classification: Primary 46E10. Secondary 30H05; 46A13; 46M40
Complex dispersion relation of a double chain of lossy metal nanoparticles

We study the propagation characteristics of optical signals in waveguides composed of a double chain of metallic nanoparticles embedded in a dielectric host. We find that the complex Bloch band diagram for the guided modes, derived by the Mie scattering theory including material losses, exhibits strong differences with respect to the previously studied single chain. The results of the model are validated through the finite element solution of the Maxwell equations.
Single shot detector application for image disease localization

Bounding box algorithms are useful in localization of image patterns. Recently, utilization of convolutional neural networks on X-ray images has proven a promising disease prediction technique. However, pattern localization over prediction has always been a challenging task with inconsistent coordinates, sizes, resolution and capture positions of an image. Several model architectures like Fast R-CNN, Faster R-CNN, Histogram of Oriented Gradients (HOG), You only look once (YOLO), Region-based Convolutional Neural Networks (R-CNN), Region-based Fully Convolutional Networks (R-FCN), Single Shot Detector (SSD), etc. are used for object detection and localization in modern-day computer vision applications. SSD and region-based detectors like Fast R-CNN or Faster R-CNN are very similar in design and implementation, but SSD have shown to work efficiently with larger frames per second (FPS) and lower resolution images. In this article, we present a unique approach of SSD with a VGG-16 network as a backbone for feature detection of bounding box algorithm to predict the location of an anomaly within chest X-ray image.
Repetition-Rate Multiplication in Actively Mode-Locked Fiber Lasers

Active mode-locking has proved to be very effective in the generation of short, high repetition rate pulse train from fiber lasers. One of the limitation, however, is that the repetition rate of the pulses becomes limited by the frequency at which modulation is performed. It is, therefore, very challenging to find ways of increasing the repetition rate of the output pulses from an actively mode locked lasers without requiring any increase in the modulation frequency. Recently, Onodera et al. [1, 2] reported a novel scheme for several-fold multiplication in the repetition rate by applying rational detuning to the modulation frequency.
Informed Prosumer Aggregator Bidding Strategy via Incorporating Distribution Grid Outage Risk Predictions

FERC Order 2222 paves the way for aggregated distributed energy resources (DERs) participation in the wholesale electricity market. A particular DER assumed to be widely available in the future is the distributed prosumer (DP), also called virtual power plant (VPP), which may host PV generation, and stationary and mobile battery energy storage systems, in addition to the on- site passive load. DP aggregation and participation in the day-ahead market ancillary service products (ASPs) require managing uncertainties associated with load consumption and photovoltaic generation, electric vehicle (EV) scheduling, market-clearance prices, etc. Outages in the distribution grid may distort these energy-limited resources from their optimal operating point, potentially impacting their ability to deliver the committed ASPs in real-time. To address these challenges, first, we develop a machine learning algorithm to predict the risk of outages in distribution feeders. Next, we incorporate the distribution feeder State of Risk (SoR) predictions with the bidding model of the DP aggregator to provide an informed decision-making tool for optimal participation in the energy and ASP markets. The simulation results demonstrate the efficacy and scalability of the proposed model in improving the aggregator profitability and preventing penalties for the inability to deliver ASPs due to unexpected energy capacity limits of DP assets.
Feature-based Map Merging with Mesh Networks in Swarm Robot Systems

In unknown environments, it is highly important to acquire efficiently the map of the unknown environments, which can be realized with swarm robot systems. However, swarm robots suffer from the lack of sensor data due to inevitably limited resources. Then, the individual maps of swarm robots degenerate as time goes, and thus the collective map of merging the individual maps may be inaccurate. This paper presents a feature-based map merging system with mesh networks to acquire individual maps efficiently and merge them accurately. The proposed system was tested with two small robots equipped with relatively low-cost sensors in unknown indoor environments. The experimental results showed that the proposed system acquired successfully individual maps and merged them accurately.
Optimal Decoupled Discontinuous Modulation for StatComs Based on the Cascaded H-Bridge Converter

Conventional discontinuous pulsewidth modulation (DPWM) strategies for cascaded H-bridge static compensators suffer from poor inter-phase capacitor voltage balance control during unbalanced grid voltage conditions. Specifically, the logic-based algorithm that calculates the zero-sequence voltage (ZSV) for discontinuous operation interacts with the closed-loop capacitor voltage control. This article proposes an optimal DPWM strategy based on a finite-set optimization that chooses the best ZSV candidate that minimizes the control interactions while clamping a converter voltage. Furthermore, the effect of the different ZSV candidates on the switching loss is also considered within the optimization. Extensive experimental study is provided to demonstrate the effectiveness of the proposed approach.
Analog Triggered Asynchronous Clocking Technique Based on the Ring Amplifier in Pipeline ADC

A design technique for the analog triggered asynchronous clocking control technique for the pipeline ADC is presented, which is convenient for the realization of highly integrated ADCs. The analog trigger technique is implemented with dynamic-power residue amplifiers such as ring amplifiers (RAMPs) inside ADC to generate the ready signal, so the asynchronous processing is realized, which solves the design problem of establishing a high-frequency clock inside the highly integrated ADCs and completes the low-power designs. Simulation results of the adopted fully-differential RAMP using 130nm CMOS process models, supply of 1.2V, and clock frequency of 200MHz. Compared with the ready signal generated by the dynamic comparator in the SAR ADC, the results show that the duty cycle generated by the RAMP is 50%, and the setting up time is 114.1ps, which is more suitable for high-speed design.
Substrate Integrated Waveguide Leaky-Wave Antenna Featuring Complete Backward Scanning

In this paper, a substrate integrated waveguide (SIW) leaky-wave antenna (LWA) is presented, which has the capability of complete backward scanning with stable backfire radiation. The proposed SIW-based LWA consists of periodic structures, in which each double-layer slotted unit is shaped by duplicating the upper nonidentical slots to the bottom layer with the same offset dy with respect to the transversal axis. By properly manipulating the dispersion diagram of the unit cell, continuous frequency scanning characteristic from backfire to broadside is realized. Within the operating band from 12.6 GHz to 18.2 GHz, the antenna works in the fast-wave band, accomplishing beam scanning from −90° to 0° with the average realized gain and radiation efficiency of 10.39 dBi and 84%.
Efficacy of different treatment protocols for endometritis in Camelus dromedarius

Endometritis is considered a significant cause of infertility problems in dromedary camels. This study aimed to compare the efficacy of different treatment protocols for endometritis in dromedary camels under Abu Dhabi Emirates' conditions. A total of 112 dromedary she-camels with uterine infection were subjected to uterine swabbing for bacterial culture and received one of the following treatments: (i) uterine douching with lotagen every other day for three doses, (ii) single parenteral oxytetracycline injection, (iii) subcutaneous injection with ceftiofur for 5 days, or (vi) combined oxytetracycline-ceftiofur injection. The results showed that Escherichia coli was the most isolated bacteria, followed by Streptococcus species. Treatment efficacy was (P < 0.05) higher in ceftiofur and oxytetracycline-ceftiofur protocols compared with lotagen and oxytetracycline protocols. The fertility indexes, services per conception and pregnancy rate, were improved in ceftiofur and mixed oxytetracycline plus ceftiofur protocols as the pregnancy rate was (P < 0.05) higher in those protocols compared with lotagen and oxytetracycline protocols (71.4 and 67.9% vs. 39.3 and 42.9%, respectively). On the other hand, the number of services per conception was significantly lower in ceftiofur and oxytetracycline-ceftiofur protocols (1.2 for each protocol) than in lotagen and oxytetracycline protocols (1.8 and 1.7, respectively). In conclusion, subcutaneous injection of 1 ml ceftiofur per 50 kg body mass for 5 days can be used as an efficient treatment for uterine infection in female dromedary camels caused by E. coli and Streptococcus species for improving their fertility indexes.
A brain-inspired unsupervised learning algorithm for SAR Target Classification

Artificial Neural Networks (ANNs) have driven remarkable progress in AI over the past decade. Based on the ability of feature extraction and the Back Propagation (BP) supervision algorithm, ANNs can achieve outstanding performance in classification tasks. However, the dependence on data limits the application of ANNs in tasks with insufficient data. Spike Timing Dependent Plasticity (STDP) is widely believed to underlie the unsupervised learning process in the brain. Inspired by STDP, this paper presents a Phase-dependent plasticity (PDP) unsupervised learning algorithm. Combined with phase information, this method can introduce STDP into the ANNs. Our method can achieve a classification accuracy of 98.47% on the MSTAR dataset. PDP unsupervised algorithm is a practical attempt to combine ANNs with Spike Neural Networks (SNNs).
Classification of Environmental Sounds Through Spectrogram-Like Images Using Dilation-Based CNN

In recent years, convolutional neural networks (CNNs) have gained remarkable success in various image and audio categorization and detection tasks. Using dilated convolution in CNN can extend the network's receptive field and improve its performance, and it can also achieve a lightweight model by compressing CNN. Environmental Sound Classification (ESC) is an essential aspect of the non-speech audio classification problem and has attracted the scientific community's interest due to the breakthrough in learning algorithms ESC. In this study, we propose a novel dilation-based CNN model from scratch and a baseline classic CNN model under the same condition and parameters. The dilation-based approach is very flexible and can be used for several standard CNNs to improve model performances. In addition, this strategy has a high training efficiency. The experimental results obtained on the publicly accessible Urbansounds8K dataset indicate that the proposed technique outperforms the classic CNN methods. Dilation-based network enhances accuracy and F1 values by around 4-9% compared to the baseline method.
Graphitization process of SiC(0001) studied by electron energy loss spectroscopy

Electron energy loss spectroscopy (EELS) is used to study the transition from the buffer layer to the first graphene layers during graphitization of SiC(0001). Graphene growth is controlled and correlated with spot profile analysis in low energy electron diffraction and x-ray photoelectron spectroscopy. In the EELS data both electronic transitions and plasmon losses are sensitive to the interface. The collective in-plane excitations show a characteristic blueshift upon graphitization, while single electron transitions with dipole moments along the surface normal are suppressed for the buffer layer. These dependencies can be used to control the number of epitaxially grown graphene layers.
New breather solutions of the model describing few-optical-cycle solitons beyond the slowly varying envelope approximation

The modified Korteweg–de Vries-sine-Gordon equation provides a general (1 + 1)-dimensional model describing few-cycle-pulse soliton propagation in two-component nonlinear media. For this model, we give its solutions in Wronskian form, which is convenient to describe interactions between solitons, breathers and their limit forms. Among these solutions, we get a stationary breather solution. Besides, the limit breather solution can provide two identical breathers traveling along the trajectories that are similar to logarithm curves rather than straight lines. As a reduction, we can also obtain solutions to the modified Korteweg–de Vries equation and the sine-Gordon equation.
The interaction between waves and a turbulent current: waves propagating with the current

This paper describes an experimental programme carried out in a laboratory channel with rough and smooth beds, to investigate the interaction between gravity waves and a turbulent current. In particular, changes induced in the mean-velocity profiles, turbulent fluctuations, bed shear stresses and wave attenuation rates are considered for a range of wave heights, keeping the wave period constant. The smooth-boundary tests were carried out as a necessary preliminary to the more-realistic rough-boundary condition. A directionally sensitive laser anemometer was used to measure horizontal, vertical, and 45° velocity components in the oscillating fluid, and an on-line minicomputer was programmed to produce ensemble averages of velocities, Reynolds stresses and wave-elevation data. The cycle was sampled at 200 separate phase positions, with 180 observations at each position. Measurements were made at up to 30 points in the vertical. Preliminary tests were carried out on the unidirectional current and on the waves alone. These show that mean-velocity profiles and turbulence parameters of the current agree satisfactorily with previous experiments, and that the waves are approximated closely by Stokes’ second-order theory. For combined wave and current tests, mean-velocity profiles are generally found to differ from those suggested by a linear superposition of wave and current velocities, a change in boundary-layer thickness being indicated. However, shear stresses at the smooth boundary are found to be described by such a linear addition.
Simulation and Performance Analysis of a Fuel Cell Hybrid Electric Vehicle

The ever-increasing global energy demand, combined with the scarcity of fossil fuels, air pollution, and greenhouse gas emissions, has pushed the globe towards the adoption of electric vehicles. The scarcity of public charging stations is a key impediment to broad adoption of electric vehicle infrastructure for charging. Hydrogen is a form of energy that can be stored and it has the power to deliver massive volumes of energy. Fuel Cells use hydrogen as their main fuel. This research paper focuses on Fuel Cell Hybrid Electric Vehicle (FCHEV), that is the combination of any energy storing element like an ultra-capacitor or battery with fuel cell to fulfill the power demand which is essential for the electric motor and the device attached to it. Here, Ultracapacitor is used along with FCEV to store energy. A Permanent Magnet Synchronous Motor (PMSM) is used here for transmission purpose. This article deals with designing and analysing the performance of the FCHEV model developed in MATLAB Simulink.
Simulations of Raman laser amplification in ionizing plasmas

By using the amplifying laser pulse in a plasma-based backward Raman laser amplifier to generate the plasma by photoionization of a gas simultaneous with the amplification process, possible instabilities of the pumping laser pulse can be avoided. Particle-in-cell simulations are used to study this amplification mechanism, and earlier results using more elementary models of the Raman interaction are verified [D. S. Clark and N. J. Fisch, Phys. Plasmas 9, 2772 (2002)]. The effects (unique to amplification in ionizing plasmas and not included in previous simulations) of blueshifting of the pump and seed laser pulses as well as the generation of a wake are observed not significantly to impact the amplification process. As expected theoretically, the peak output intensity is found to be limited to I∼1017 W/cm2 by forward Raman scattering of the amplifying seed. The integrity of the ionization front of the seed pulse against the development of a possible transverse modulation instability is also demonstrated.