Miracle-dz/UniFAR-FTUs huggingface dataset:
Measurements of sputtered neutrals and ions and investigation of their roles on the plasma properties during rf magnetron sputtering of Zn and ZnO targets

Langmuir probe and optical absorption spectroscopy measurements were used to determine the line-integrated electron density, electron temperature, and number density of Ar atoms in metastable 3P2 and 3P0 levels in a 5 mTorr, rf magnetron sputtering plasmas used for the deposition of ZnO-based thin films. While the average electron energy and density of Ar atoms in 3P2 and 3P0 excited states were fairly independent of self-bias voltage, the Ar 3P2-to-electron number density ratio decreased by approximately a factor of 5 when going from −115 V to −300 V. This decrease was correlated to an increase by about one order of magnitude of the number density of sputtered Zn atoms determined by absolute actinometry measurements on Zn I using either Ar or Xe as the actinometer gas. These results were also found to be in excellent agreement with the predictions of a global model accounting for Penning ionization of sputtered Zn particles. The importance of the latter reactions was further confirmed by plasma sampling mass spectrometry showing a double peak structure for Zn ions: a low-energy component ascribed to thermalized ions created in the gas phase (by direct electron impact and by Penning ionization) and a high-energy tail due to ions ejected from the target and reaching quasi-collisionlessly the substrate surface.Langmuir probe and optical absorption spectroscopy measurements were used to determine the line-integrated electron density, electron temperature, and number density of Ar atoms in metastable 3P2 and 3P0 levels in a 5 mTorr, rf magnetron sputtering plasmas used for the deposition of ZnO-based thin films. While the average electron energy and density of Ar atoms in 3P2 and 3P0 excited states were fairly independent of self-bias voltage, the Ar 3P2-to-electron number density ratio decreased by approximately a factor of 5 when going from −115 V to −300 V. This decrease was correlated to an increase by about one order of magnitude of the number density of sputtered Zn atoms determined by absolute actinometry measurements on Zn I using either Ar or Xe as the actinometer gas. These results were also found to be in excellent agreement with the predictions of a global model accounting for Penning ionization of sputtered Zn particles. The importance of the latter reactions was further confirmed by plasma sampling .
Effect of Wastewater Composition on the Development of an Activated Sludge Biological Phosphorus Removal System

A biological system for P removal has been developed by using an A/O (anaerobic/aerobic) activated sludge process with a sequencing batch reactor operation mode. The effect of three kinds of synthetic wastewater with different organic composition has been studied. Evolution of sludge and effluent characteristics from the original sludge to steady state conditions were studied, and P and COD profiles during batch A/O cycles were also analysed. A fast P accumulation in the sludge was detected during the previous acclimation phases. The presence of higher concentrations of easily biodegradable products improved the acclimation process and increased the rate at which a conventional activated sludge was transformed into a phosphorus accumulating microorganism enriched sludge. The steady state P content of the sludge increased and the VSS concentration decreased in all cases. Acetate in wastewater caused bad sludge settling and soluble starch caused slow evolution to steady state conditions. Different stoichiom.
N2O ionization and dissociation dynamics in intense few cycle femtosecond laser radiation

Using few cycle pulses, uniform-electric-field-ion imaging spectrometer and Dalitz plotting, we can identify two new stepwise processes, in the dissociation of the 3+ and 4+ states of N2O in intense few cycle pulses at 4 × 1015 Wcm−2. We observe suppression of selective channels at longer pulse length, which we attribute to molecular dynamics on the 2+ state and the shape of the 3+ potential, which influences propagation of the dissociating wave packet.
Investigation of molecular interaction between single‐walled carbon nanotubes and conjugated polymers

Single-walled carbon nanotubes (SWNTs) have unique properties such as high electrical conductivity and high tensile strength. Their composites with polymers have a great role in new sciences such as organic solar cells and ultrastrong lightweight materials. In this article, molecular dynamic simulations with polymer consistent force field are performed to study the interaction between SWNTs and conjugated polymers including poly(2-methoxy-5-(3-7-dimethyloctyloxy)-1,4-phenylenevinylene) (MDMO-PPV), poly(3-hexythiophene) (P3HT), and poly[(9,9′-dioctylfluorenyl-2,7-diyl)-co-bis(N,N′-(4,butylphenyl))bis(N,N′-phenyl-1,4-phenylene)diamine] (PFB). We computed the interaction energy and morphology of polymers adsorbed to the surface of SWNTs was studied by the radius of gyration (Rg). The influence of important factors such as SWNT radius, chirality, and the temperature on the interfacial adhesion of SWNT–polymer and Rg of polymers were studied. We found that the strongest interaction between the SWNTs and these polymers was, first observed for P3HT, then MDMO-PPV, and finally PFB. Our results showed that the interaction energy is influenced by SWNT radius and the specific monomer structure of the polymers, but the effects of chirality and temperature are very weak. In addition, we found that the temperature, chirality, and radius have not any important effect on the radius of gyration. POLYM. COMPOS. ,, 2012. © 2012 Society of Plastics Engineers
Fast and Robust Iterative Closest Point

The iterative closest point (ICP) algorithm and its variants are a fundamental technique for rigid registration between two point sets, with wide applications in different areas from robotics to 3D reconstruction. The main drawbacks for ICP are its slow convergence, as well as its sensitivity to outliers, missing data, and partial overlaps. Recent work such as Sparse ICP achieves robustness via sparsity optimization at the cost of computational speed. In this paper, we propose a new method for robust registration with fast convergence. First, we show that the classical point-to-point ICP can be treated as a majorization-minimization (MM) algorithm, and propose an Anderson acceleration approach to speed up its convergence. In addition, we introduce a robust error metric based on the Welsch’s function, which is minimized efficiently using the MM algorithm with Anderson acceleration. On challenging datasets with noises and partial overlaps, we achieve similar or better accuracy than Sparse ICP while being at least an order of magnitude faster. Finally, we extend the robust formulation to point-to-plane ICP, and solve the resulting problem using a similar Anderson-accelerated MM strategy. Our robust ICP methods improve the registration accuracy on benchmark datasets while being competitive in computational time.
Hybrid Federated Learning: Algorithms and Implementation

Federated learning (FL) is a recently proposed distributed machine learning paradigm dealing with distributed and private data sets. Based on the data partition pattern, FL is often categorized into horizontal, vertical, and hybrid settings. Despite the fact that many works have been developed for the first two approaches, the hybrid FL setting (which deals with partially overlapped feature space and sample space) remains less explored, though this setting is extremely important in practice. In this paper, we first set up a new model-matching-based problem formulation for hybrid FL, then propose an efficient algorithm that can collaboratively train the global and local models to deal with full and partial featured data. We conduct numerical experiments on the multi-view ModelNet40 data set to validate the performance of the proposed algorithm. To the best of our knowledge, this is the first formulation and algorithm developed for the hybrid FL.
Mass Transfer Characteristics between Molten Steel and Particles under Conditions of RH-PB(IJ) Refining Process

The mass transfer characteristics between liquid steel and powder particles in RH-PB(IJ) refining process have been investigated on a water model of 1/4 linear scale for a 150 t multifunction RH degasser. Sodium chloride powder with analytical purity has been utilized as the flux for injection. The mass transfer coefficient (k) of solute (NaCl) in the liquid has been determined under the conditions of the RH-PB(IJ) process. The effects of the main technological and structural parameters on the characteristics have been examined. It may be concluded from the results that, under the conditions of the present work, the mass transfer coefficient in the liquid increases with increasing the lifting gas flow rate, with increasing the inner diameter of the upsnorkel, with increasing the circulation rate of the liquid, and with increasing the particle size of powdered flux, and decreases with an increase in the inner diameter of the downsnorkel. Its value is in the range of (3.392×10−5–2.661×10−4) m/s. The corresponding dimensionless relationships for the mass transfer coefficient in the range were obtained. Taking the relative velocity of the particles to the liquid into account, the mass transfer in the liquid may be characterized bySh=2+0.0285(Res)3/4Sc1/3Considering the energy dissipation caused by the fluctuation in the velocity of the liquid in turbulent flow, the following dimensionless relationship has been reached:Sh=2+0.0285(esldp4/vl3)1/4Sc1/3When the mass transfer is regarded as that between rigid bubbles and molten steel, it may be characterized by:Sh=2+0.00731[Res0.48Sc0. 339(g1/3dp/D2/3)0.072]1.455In comparison with the mass transfers coefficient in the molten steel between the powder particles and the liquid in RH-PTB process, that in the conditions of RH-PB(IJ) refining is smaller, being about 1/4–1/3 of the former, but the both have a similar feature and pattern.
Attenuation of microwaves propagating through parallel-plate helium glow discharge at atmospheric pressure

The experimental study of microwave-plasma interaction has been performed to demonstrate the transmission and attenuation of microwaves in atmospheric pressure glow discharge plasma. The cold-collisional plasma produced at atmospheric pressure can absorb the microwave energy because of its complex dielectric constant. The microwave of 10 GHz frequency was launched into the plasma and attenuation was measured as a function of electron plasma density, plasma thickness, electron-neutral collision frequency, etc. It was observed that the attenuation significantly depends on electron plasma density and thickness. The microwave attenuation measurement was also used as a diagnostic to estimate electron plasma density. It was validated by optical emission spectroscopic measurements with helium line intensity ratio method. Both the methods show good agreement.
LED-ID detection and recognition method based on optical camera communication using discrete Fourier transform

Abstract. Optical camera communication (OCC) traditionally uses the bright and dark stripes of a rolling shutter pattern captured by the complementary metal–oxide–semiconductor image sensor to realize communication. We assign a unique identification [LED’s unique identification (LED-ID)] to each LED and introduce an LED-ID detection and recognition method of OCC using discrete Fourier transform (DFT). It is different from the traditional LED modulation and demodulation method. In this approach, LED-IDs are modulated to possess different frequency characteristics instead of transmitting data. Taking the DFT of the rolling shutter pattern to obtain a spectrum image, we can recognize the LED-ID according to the characteristics of the spectrum image. The experiment results show that the proposed method has good performance, with at least 426 recognizable LED-IDs and a recognition distance reaching 3 m. Therefore, the proposed method can be considered as one of the effective methods for OCC.
Region-aware multi-resolution learning for vehicle re-identification using mask

Abstract. As an instance-level recognition problem, the key to effective vehicle re-identification (Re-ID) is to carefully reason the discriminative and viewpoint-invariant features of vehicle parts at high-level and low-level semantics. However, learning part-based features requires a laborious human annotation of some factors as attributes. To address this issue, we propose a region-aware multi-resolution (RAMR) Re-ID framework that can extract features from a series of local regions without extra manual annotations. Technically, the proposed method improves the discriminative ability of the local features through parallel high-to-low resolution convolutions. We also introduce a position attention module to focus on the prominent regions that can provide effective information. Given that the vehicle Re-ID performance can be affected by background clutters, we use the image obtained through foreground segmentation to extract local features. Results show that using original and foreground images can enhance the Re-ID performance compared with using either the original or foreground images alone. In other words, the original and foreground images complement each other in the vehicle Re-ID process. Finally, we aggregate the global appearance and local features to improve the system performance. Extensive experiments on two publicly available vehicle Re-ID datasets, namely, VeRi-776 and VehicleID, are conducted to validate the effectiveness of each proposed strategy. The findings indicate that the RAMR model achieves significant improvement in comparison with other state-of-the-art methods.
Spatially adaptive hybrid variational model for temperature-dependent nonuniformity correction of infrared images

Abstract. The restoration of nonuniform distorted infrared (IR) images is crucial for human visual perception and subsequent application tasks. However, existing methods sometimes fail to yield visually natural decompositions and perform insufficiently in the preservation of meaningful structures while suppressing disturbing noise. A spatially adaptive hybrid ℓ1 − ℓ2 variational framework for the nonuniform intensity correction of IR images is proposed. Considering the piecewise constant characteristics of latent images, a weighted ℓ1-norm regularization method is developed to constrain the local affinity of neighborhood pixels according to their intensity and structural priors, thereby significantly preserving structures while smoothly flattening areas. Additionally, an ℓ2-norm guided local smoothness constraint is incorporated with an absolute scale term provided by coarse estimation to characterize the bias field component to restrict potential solutions and enforce the bias component to be textureless. Moreover, the proposed ℓ1 − ℓ2 model is efficiently solved by an alternating direction method of multipliers scheme. Extensive experiments on both synthesized images and two real-world IR datasets indicate that the performance of the proposed method is superior to that of five existing algorithms both visually and numerically.
Single-pixel postprocessing-free 5 Mbps quantum random number generator using a single-photon avalanche diode detector and a T/(T − t) pulse-shaped laser driver

Abstract. Experimental demonstration of a quantum random number generator based on one single-photon avalanche diode (SPAD) detector, a T / ( T − t ) pulse-shaped laser, and an field-programmable gate array (FPGA) acquisition module is presented. An integrated laser driver drives an external laser diode at 670 nm wavelength, whereas the SPAD with a photon detection probability of 18.5% is integrated together with an active quenching-resetting circuit. The SPAD detector generates counts for the interarrival time (IAT) measurement system implemented in an FPGA, where the change of the IATs between consecutive pulses is used to derive a random bit stream. It is shown how the application of a pulse-shaped laser driver can increase the performance of the system as compared to the continuous-wave operation of the laser diode to achieve the maximum generation rate of 5 Mbps while using a single SPAD. The generated numbers pass all randomness tests of the National Institute of Standards and Technology (NIST), Dieharder, and ENT test (pseudorandom number sequence test) suits.
Analytical design method of three-mirror anastigmatic telescope with mirror spacings as free design parameters

Abstract. We present an analytical design method for the three-mirror anastigmatic (TMA) telescope with mirror spacings as the free design parameter. After the optical designer determines, the system focal length and the mirror spacings according to the design requirements, the design solutions of all TMA telescopes that meet the conditions can be obtained directly according to the formulas for the mirror radius and conic constants derived. The method here can predetermine the mirror position and system envelope size before design, and can quickly give all design solutions. We give a design example using the method and compare and discuss all design solutions of TMA.
Attn-Eh ALN: complex text-to-image generation with attention-enhancing adversarial learning networks

Abstract. Text-to-image generation can be widely applied in various fields, such as scene retrieval and computer-aided design. The existing approaches can generate realistic images from simple text descriptions, whereas rendering images from complex text descriptions is still not satisfactory for practical applications. To generate accurate high-resolution images from given complex texts, we proposed an attention-enhancing adversarial learning network (Attn-Eh ALN) based upon conditional generative adversarial networks and the attention mechanism. This model consists of an encoding module and a generative module. In the encoding module, we proposed a local attention driven encoding network that allows words in the text with different weights to enhance the semantic representation of specific object features. The attention mechanism is employed to capture more details while ensuring global information. This enables the details in the generated images to be more fine-grained. In the discriminating stage, we take multiple discriminators to distinguish the realness of the generated images, avoiding the bias caused by a single discriminator. Moreover, a semantic similarity judgment module is introduced to improve the semantic consistency between the text description and visual content. Experimental results on benchmark datasets indicate that Attn-Eh ALN generates favorable results in comparison with other state-of-the-art methods from qualitative and quantitative assessments.
PLA/Kenaf/APP Biocomposites: Effect of Alkali Treatment and Ammonium Polyphosphate (APP) on Dynamic Mechanical and Morphological Properties

Kenaf-filled polylactic acid (PLA) biocomposites were prepared using dry blending, twin screw extrusion and compression molding. PLA was blended with raw and alkali treated kenaf, polyethylene glycol and ammonium polyphosphate (APP). Dynamic mechanical properties of biocomposites were investigated by dynamic mechanical analysis. Storage modulus of composites decreased, while magnitude of damping peaks increased with increase in APP content. The T g of composites shifted to lower values with APP addition. Alkali treatment improved interfacial adhesion between PLA and kenaf. SEM analysis indicates good dispersion of APP in PLA matrix, however interfacial adhesion between PLA and matrix decreased with increasing APP content.
A rechargeable zinc-air battery based on zinc peroxide chemistry

When two is better than four Batteries based on the reaction of zinc and oxygen have been used for more than a century, but these have been primary (that is, nonrechargeable) cells. These batteries use an alkaline electrolyte and require a four-electron reduction of oxygen to water, which is a slow process. Sun et al. show that with the right choice of nonalkaline electrolyte, the battery can operate using a two-electron zinc-oxygen/zinc peroxide chemistry that is far more reversible. By making the electrolyte hydrophobic, water is excluded from the near surface of the cathode, thus preventing the four-electron reduction. These batteries also show higher energy density and better cycling stability. Science, this issue p. 46 Use of trifluoromethane sulfonate in place of basic electrolyte enables electrochemical reversibility of zinc-air batteries. Rechargeable alkaline zinc-air batteries promise high energy density and safety but suffer from the sluggish 4 electron (e−)/oxygen (O2) chemistry that requires participation of water and from the electrochemical irreversibility originating from parasitic reactions caused by caustic electrolytes and atmospheric carbon dioxide. Here, we report a zinc-O2/zinc peroxide (ZnO2) chemistry that proceeds through a 2e−/O2 process in nonalkaline aqueous electrolytes, which enables highly reversible redox reactions in zinc-air batteries. This ZnO2 chemistry was made possible by a water-poor and zinc ion (Zn2+)–rich inner Helmholtz layer on the air cathode caused by the hydrophobic trifluoromethanesulfonate anions. The nonalkaline zinc-air battery thus constructed not only tolerates stable operations in ambient air but also exhibits substantially better reversibility than its alkaline counterpart.
Evolution of fold switching in a metamorphic protein

One sequence encoding two structures Most proteins have stable, folded structures, but there are rare examples of metamorphic proteins that can switch between two different folds that may each have a different function. Dishman et al. investigated the evolution of XCL1, which is a member of the chemokine family that interconverts between the chemokine fold and a second, noncanonical fold that forms dimers. The authors used nuclear magnetic resonance spectroscopy to investigate the structures of inferred evolutionary ancestral sequences. Their results suggest that XCL1 evolved from an ancestor with the chemokine fold and then transitioned to prefer the noncanonical fold before reaching the modern-day metamorphic protein. Science, this issue p. 86 The human protein XCL1 evolved to switch between two completely different folds with different functions. Metamorphic proteins switch between different folds, defying the protein folding paradigm. It is unclear how fold switching arises during evolution. With ancestral reconstruction and nuclear magnetic resonance, we studied the evolution of the metamorphic human protein XCL1, which has two distinct folds with different functions, making it an unusual member of the chemokine family, whose members generally adopt one conserved fold. XCL1 evolved from an ancestor with the chemokine fold. Evolution of a dimer interface, changes in structural constraints and molecular strain, and alteration of intramolecular protein contacts drove the evolution of metamorphosis. Then, XCL1 likely evolved to preferentially populate the noncanonical fold before reaching its modern-day near-equal population of folds. These discoveries illuminate how one sequence has evolved to encode multiple structures, revealing principles for protein design and engineering.