Miracle-dz/UniFAR-FTUs huggingface dataset:
Transition-diffracted radiation and the C

The x-ray radiation emitted by a charged particle as it penetrates a perfect crystal is studied. We find that in addition to the already known Cerenkov radiation peak, there is a second peak which is due to the dynamical diffraction of the electromagnetic field associated with the electron. The theory developed here, which is an extension of the dynamical theory of x-ray diffraction, allows us to treat situations in which the direction of incidence of the electron, as well as the orientation of the crystal surface relative to the crystal planes, are kept arbitrary. Our equations apply also to situations in which the Bragg angle is close to {pi}/2, where several of the approximations usually made in the dynamical theory are known to fail. Various features such as intensities, direction, frequency, and the spectral and angular widths of both the Cerenkov and the transition-diffracted'' radiation are studied. A geometrical construction of the dispersion surfaces has been found to be very useful in visualizing the content of the theory. It is possible that these two processes of emission may find application as a tunable source of monochromatic and very directional x rays.
A comparative study of the effect of transparent conducting oxides on the performance of Cu 2 ZnSnS 4 thin ﬁlm solar cell

One major factor affecting the performance of the kesterite Cu 2 ZnSnS 4 (CZTS) thin ﬁlm solar cell is its low open circuit voltage ( V oc ). In solar cells, transparent conducting oxides are components which act as electrode elements and their work functions control the open circuit voltage of the device. In this work, numerical modeling and simulation has been used to study the effect of various TCOs ﬂuorine-doped tin oxide (FTO), aluminum-doped zinc oxide (AZO) and indium tin oxide (ITO), on the performance characteristics of CZTS thin ﬁlm solar cell. The usage of ITO gave the best performing device with a conversion efﬁciency of 9.98%, followed by AZO with 8.41% and FTO with 5.91%. Further optimization of some of the parameters of AZO and FTO shows that they are good alternative to the very expensive ITO. The effect of the variation in operating temperature indicates that AZO and FTO have better thermal stability. In addition, reduction in device thickness, application of FTO/AZO double layer and the ﬁltering of the illumination within the visible spectrum enhanced the overall device performance which yielded an efﬁciency of 14.46%.
Influential observations in principal component analysis:a case study

A number of results have been derived recently concerning the influence of individual observations in a principal component analysis. Some of these results, particularly those based on the correlation matrix, are applied to data consisting of seven anatomical measurements on students. The data have a correlation structure which is fairly typical of many found in allometry. This case study shows that theoretical influence functions often provide good estimates of the actual changes observed when individual observations are deleted from a principal component analysis. Different observations may be influential for different aspects of the principal component analysis (coefficients, variances and scores of principal components); these differences, and the distinction between outlying and influential observations are discussed in the context of the case study. A number of other complications, such as switching and rotation of principal components when an observation is deleted, are also illustrated.
First-principles investigation on transport properties of Zn 2 SnO 4 molecular device and response toward NO 2 gas molecules

The transport properties of a Zn 2 SnO 4 device along with adsorption properties of NO 2 gas molecules on Zn 2 SnO 4 (ZTO) molecular devices are investigated with density functional theory using the non-equilibrium Green’s function technique. The transmission spectrum and device density of states spectrum conﬁrm the changes in HOMO– LUMO energy level due to transfer of electrons between the ZTO-based material and the NO 2 molecules. I – V character-isticsdemonstratethevariationinthecurrentuponadsorption of NO 2 gas molecules on the ZTO device. The ﬁndings of the present study clearly suggest that ZTO molecular devices can be used to detect NO 2 gas molecules in the trace level.
Harmonic functions of polynomial growth on complete manifolds II

Let $M$ be a complete noncompact Riemannian manifold of dimension $m$ . For a nonnegative number $d$ , we denote by $\mathcal{H}_{d}(M)$ the space of harmonic functions $h$ of polynomial growth of order $d$ , namely, $|h|\leqq Ar^{f}(+B$ for some positive constants $A$ and $B$ , where $r$ stands for the distance function to a fixed point, say $0$ , of $M$ . In this paper, we say that $M$ has the strong Liouville property if the dimension of $\mathcal{H}_{(f}(M)$ is finite for any $d$ (cf. [19]). It is known that the strong Liouville property holds on $M$ , for example, if $M$ is so called an asymptotically (locally) Euclidean space (cf. [2], [3], [19], [22] and the references therein), or if $m=2$ and the total curvature is finite (cf. [14], [21]). The purpose of this paper is to give some geometric conditions under which $M$ has the strong Liouville property. Our first result is stated in the following
Characterizations of semisimple classes

Abstract Two characterizations of semisimple classes of associative and alternative rings (and semigroups with 0) are given: (i) A class is a semisimple class if and only if it is hereditary, closed under extensions and subdirect sums; (ii) A class is a semisimple class if and only if it is hereditary, closed under extensions, and has the co-inductive property. The first characterization sharpens Armendariz's (1968) result proved for associative rings, the second one is categorically dual to a characterization of radical classes due to Amitsur (1954).
PALS laser energy transfer into solid targets and its dependence on the lens focal point position with respect to the target surface

This paper is devoted to investigations of laser energy transfer into solid targets with respect to the focusing lens focal point position relative to the solid target surface as obtained at the PALS laser facility. The third harmonic of the PALS laser beam with energy ~90 J and pulse duration ~250 ps (FWHM) was used for irradiation of two kinds of targets made of Cu: a slab and a 3.6 µm thick foil. The focal point of the beam was located either inside or in front of the target surface, and care was taken to ensure the same laser spot radii in both cases (250 µm). It was demonstrated that these two opposite focal point positions give rise to significantly different laser-plasma interactions: with either depression or maximum of the laser intensity distribution in the center of the beam, respectively. It was also verified that the focal point position inside of the target is favorable for plasma jets creation, whereas the opposite case is more effective for acceleration of flyers.
Janus MoSSe monolayer coordinated single B atom as an efficient catalyst for nitrogen reduction to ammonia

Electrochemical nitrogen fixation under ambient conditions is an energy-saving and environmental-friendly method alternative to the Haber-Bosch process, but is subjected to efficient electrocatalysts. Through density functional theory (DFT) computations, we systematically investigate the NRR performance of single B atom substitution S and Se atom in the Janus MoSSe monolayer (BSMoSSe and BSeMoSSe) as a single atom catalyst (SAC). The results show that BSMoSSe and BSeMoSSe are promising catalysts with a low energy barrier of 0.10 eV and 0.27 eV and excellent NRR selectivity. Charge density differences confirmed the N2 activation mechanism of acceptance-donation between B and adsorbed N2. These findings bring a new strategy for NH3 production by BSMoSSe and BSeMoSSe electrocatalysts under ambient conditions.
Mongolian-Chinese Machine Translation Based on Graph Neural Network

Most of the current Mongolian-Chinese neural machine translation relies on a sequence-to-sequence-based encoder-decoder, which does not effectively utilize the syntactic information of sentences as well as the hierarchical information of the language. To solve this problem, a graph-to-sequence-based encoder-decoder is constructed by introducing graph neural networks, making better use of syntactic information and semantic knowledge of sentences. We will build a Mongolian dependency tree library and design a densely connected graph convolutional neural network (D-GCN) based on GCN combined with a densely connected network (DenseNet). Experiments are conducted to compare with the sequence-to-sequence based Mongolian-Chinese neural machine translation model and the variant model of graph neural network, and the results verify the advantages of the D-GCN-based Mongolian-Chinese neural machine translation model in translation performance.
APIGAN: Learning to Recommend Java API in Real-Time Using Generative Adversarial Networks

In order to improve the accuracy of API recommendations, this paper proposes a novel API recommendation approach of APIGAN fully leveraging structural and textual information based on Generative Adversarial Networks, in which a Long Short-Term Memory (LSTM) is used as a generator while a Convolutional Neural Network (CNN) is used as a discriminator. The structural and semantic information of a source code extracted from an abstract syntax tree is used to construct a program dependence graph (PDG) which is also the input of the generator and the discriminator. By evaluating the difference in outputs of them, LSTM is evolved gradually till an optimized program dependence network is obtained to recommend top-k APIs. The results of the experiments show that APIGAN outperforms state-of-the-art research such as APIREC, GraLan, and n-gram in the aspect of top-k accuracy.
Robust Map Merging Method for Collaborative LiDAR-based SLAM Using GPS Sensor

Typical lidar-based mappings need to cover the entire environment alone, which often leads to long build cycles and large computational resource requirements. Collaborative simultaneous localization and mapping have been applied to explore large and complex scenarios. However, merging local maps from multiple robots remains a challenge. It is crucial for Collaborative SLAM to identify overlapping areas and obtain the transformation matrix for map merging. To this end, this paper proposes a map merging method for collaborative lidar-based SLAM based on GPS measurements and improved Iterative Closest Point (ICP). We add a GPS sensor to the traditional robot configuration and use a simplified model to convert latitude and longitude data into plane coordinate data. According to Euclidean geometry, we determine the overlapping regions scanned by robots and calculate the initial pose transformation matrix between different robots. Based on the traditional ICP algorithm, KD-tree and normal vectors are used to register point clouds in overlapping regions accurately. The transformation matrix obtained by precise registration is used to rotate and translate the source local point cloud, so as to obtain the global point cloud map. In the real-world experiment, the initial transformation matrix is successfully obtained based on GPS measurements, which provides a good initial pose for the ICP algorithm. Compared with the ICP algorithm, the time consumption and RMSE of the improved ICP algorithm are reduced by 26.3% and 7.94%, respectively. Experimental results demonstrate that the proposed method can achieve accurate and efficient map fusion for multi-robot collaborative SLAM.
Emphasis of Sound Sources Using Nonnegative Matrix Factorization Based on Stereo Localizations

In this study, we emphasized sound sources using nonnegative matrix factorization (NMF) with the likelihood of the directions obtained from the estimated localizations. NMF is one of the most commonly used techniques for the separation of music signals. The emphasis of sound sources by NMF has several problems: the uncertainty of the decomposition of the bases corresponding to the sources and the necessity to group the obtained bases according to the sources. These problems have to be solved simultaneously to improve the separation performance. In order to simultaneously solve these problems, we proposed a novel NMF incorporating the cost based on the likelihood of the localizations. According to the experimental results, we could improve the separation performance by using our proposed method.
Design considerations for hardware implementation of nanoseconds time synchronization low-cost system based on precise time protocol

Precise time synchronization is the key for coordinating every node of the distributed system to complete tasks. The widespread use of Field Programmable Gate Array (FPGA) in distributed nodes has a positive effect on improving time synchronization accuracy. Although the use of FPGA could significantly improve time synchronization accuracy, there is not a universal design guideline. This work has analyzed and summarized three factors that should be considered when building a low-cost clock synchronization system using FPGA: where the timestamp should be generated, the calculation and correction of time offset, and how to handle Precise Time Protocol (PTP) messages. Based on these design considerations, the time synchronization system intellectual property (IP) core was constructed. The synchronization accuracy experiments have been performed on Zynq system-on-chip (SoC) evaluation boards of different architectures. The experimental results demonstrated that the time synchronization system constructed in this article could achieve nanoseconds accuracy.
Human Pose Estimation: Multi-stage Network Based on HRNet

Multi-stage network uses stacked networks to enhance the feature extraction capability, and can gradually refine the keypoints with the information of previous stages’ output. Obviously, multi-stage networks are more suitable for human pose estimation. However, most current multi-stage networks use a codec structure as the backbone in which downsample will cause information loss. HRNet maintains high-resolution features to supply the information which is lost in down-sampling stage. In this regard, we propose a novel two-stage network with HRNet as the backbone and stacked codec structure. HRNet has more efficient feature extraction capability, and the stacked codec network can utilize the multi-scale features generated by HRNet more effectively. This method obtains a 1.2AP improvement compared to HRNet and a significant improvement compared to other two-stage networks.
Theoretical study of the 3H(p, e + e −)4He and 3He(n, e + e −)4He processes and the X17 anomaly

The unexpected observation of eccess of events in the angular distribution of e−e+ pairs in various nuclear transitions has spurred a large interest, both experimentally and theoretically. This eccess has been interpreted as the possible existence of a new bosonic particle, the so-called X17, of mass around 17 MeV. In the present work, we investigate theoretically the possible effects of the presence of the X17 in the 3H(p, e + e −)4He and 3H(n, e + e −)4He reactions. For these processes it is possible to compute accurate ab initio bound- and continuum-states wave functions, so the existence of X17 can be unambigously revealed. Moreover, by exploiting the rich structure of the 4He spectrum, it is possible to determine its quantum number, as, for example, if it is either a scalar, a pseudoscalar, a vector, or an axial particle.
Life evaluation of rolling element bearings using stochastic neighbor embedding deep regression

Accurate residual service life (RSL) evaluation of rolling element bearings is significant for prognostics and health management to guarantee rotating machinery safety, availability, and efficiency. This work develops a method called stochastic neighbor embedding deep regression (SNEDR) to enhance the estimation performance of the RSL. First, the appropriate features originating from the vibration data of the tested REB are extracted. The state indicators are subsequently established with the extracted features by introducing the stochastic neighbor embedding. By doing that, the random errors and noises generated from the vibration signals can be minimized, and the evaluation performance may be improved. Finally, the regression model based on the state indicators and the long short-term memory network with time information representation capacity is generated for the RSL evaluation. The availability of the SNEDR is validated by the real data derived from a bear failure experiment. Furthermore, a peer method is introduced for a comparative study. Experimental results show that the SNEDR outperforms the competing method and can yield more reasonable and accurate evaluation results.
An Improved Gesture Recognition Model Based on Mini-Xception

With the rapid development of artificial intelligence technology, gestures have become the mainstream in the field of human-computer interaction because of their simplicity, easy understanding and non-contact. Compared with the early data gloves, the vision-based non-contact gesture recognition interaction method has obvious advantages. However, the variability of the gesture itself, the complexity of the background and the influence of different lighting conditions have impacted the accuracy of gesture recognition. With the rapid development of deep learning technology, gesture recognition has achieved amazing results in accuracy. To improve gesture recognition accuracy in complex background, this paper optimizes the mini-xception network model of lightweight convolutional neural network algorithm, introduce the transfer learner and integrate YOLOV4-tiny into the mini-xception model, generate a new network model YT_ mini-Xception. After experimental verification, by YT_ Mini-xception network model, the average accuracy of 0-9 gesture recognition on complex background data set is 96.64%, the average recognition time was 39.8 milliseconds, and the expected goal was achieved.
Lattice Boltzmann Simulations of Thermocapillary Motion of Droplets in Microfluidic Channels

Our recently developed lattice Boltzmann model is used to simulate droplet dynamical behaviour governed by thermocapillary force in microchannels. One key research challenge for developing droplet-based microfluidic systems is control of droplet motion and its dynamic behaviour. We numerically demonstrate that the ther- mocapillary force can be exploited for microdroplet manipulations including synchro- nisation, sorting, and splitting. This work indicates that the lattice Boltzmann method provides a promising design simulation tool for developing complex droplet-based microfluidic devices. AMS subject classifications :7 6T99
Bias from heterogeneous usage of space in spatially explicit capture–recapture analyses

Royle et al. (Methods in Ecology and Evolution, , 4, 520) proposed a spatially explicit capture–recapture (SECR) model in which an animal's usage of a site, and hence its probability of detection, depends on a function of site‐specific covariates normalized using a weighted sum of such values across the animal's home range. From simulations supposedly based on the model, they drew the conclusion that existing methods will produce ‘extremely biased’ estimates of population size when animals use space selectively. This conclusion is faulty because they simulated data from a different model, omitting the normalization needed to represent selection of resources at the home‐range level. New simulations show that the null SECR estimator of population size is nearly unbiased for low to moderate levels of selective space use when the generating model includes normalization. Including detector‐level covariates of detection, as allowed in standard software, nearly eliminates bias due to strongly selective space use, whether or not the generating model includes normalization.
Interaction of ultrahigh laser fields with beams and plasmas

The nonlinear interaction of ultraintense laser pulses with electron beams and plasmas is rich in a wide variety of new phenomena. Advances in laser science have made possible compact terawatt lasers capable of generating subpicosecond pulses at ultrahigh powers (≥1 TW) and intensities (≥1018 W/cm2). These ultrahigh intensities result in highly relativistic nonlinear electron dynamics. This paper briefly addresses a number of phenomena including (i) laser excitation of large‐amplitude plasma waves (wake fields), (ii) relativistic optical guiding of laser pulses in plasmas, (iii) optical guiding by preformed plasma channels, (iv) laser frequency amplification by ionization fronts and plasma waves, (v) relativistic harmonic generation, (vi) stimulated backscattering from plasmas and electron beams, (vii) nonlinear Thomson scattering from plasmas and electron beams, and (viii) cooling of electron beams by intense lasers. Potential applications of these effects are also discussed.
Implementation of TCM grid-connected inverter based on STM32

In this paper, STM32 is used to realize the control of TCM grid-connected inverter, which replaces the traditional control mode of digital logic controller and MCU combination, and simplifies the controller structure. A simple method for calculating the negative driving voltage of gallium nitride is presented. In this paper, the circuit parameters of each part of TCM inverter are designed, and the design scheme of each part of the circuit is given. Finally, a 200W prototype is built to verify the feasibility of the design scheme.
Realization of the MIDI cold optics

MIDI is the Mid-Infrared interferometer for ESO's VLTI (Very Large Telescope Interferometer), which has been developed by a German-Dutch-French consortium [MPIA Heidelberg Germany, NOVA/ASTRON Dwingeloo Netherlands, Observatoire de Meudon France]. The initial aim of MIDI is to combine the beams from 2 telescopes in the 10 micron N-band with a spatial resolution of up to 10 milli-arcseconds and a maximum spectral resolution of 230. Modulation of the optical path difference can be done using piezo-driven mirrors at room temperature, but beam combination and detection of the interferometric signal has to be done at cryogenic temperatures due to the 'thermal' wavelength domain. The MIDI cold bench is therefore mounted inside a cryostat, cooled by means of a closed cycle cooler to about 40K for the cold optics and 8K for the detector. The design of the cold optics has been kept as simple as possible, creating challenges such as preserving alignment from 295K to 40K and accessibility. This poster describes the realization of the cold optics, the alignment and test strategies and laboratory results.