Phase-resolved NuSTAR and Swift-XRT Observations of Magnetar 4U 0142+61

We present temporal and spectral analysis of simultaneous 0.5-79 keV Swift-XRT and NuSTAR observations of the magnetar 4U 0142+61. The pulse profile changes significantly with photon energy between 3 and 35 keV. The pulse fraction increases with energy, reaching a value of ~20%, similar to that observed in 1E 1841-045 and much lower than the ~80% pulse fraction observed in 1E 2259+586. We do not detect the 55-ks phase modulation reported in previous Suzaku-HXD observations. The phase-averaged spectrum of 4U 0142+61 above 20 keV is dominated by a hard power law with a photon index, $\Gamma$ ~ 0.65, and the spectrum below 20 keV can be described by two blackbodies, a blackbody plus a soft power law, or by a Comptonized blackbody model. We study the full phase-resolved spectra using the electron-positron outflow model of Beloborodov (2013). Our results are consistent with the parameters of the active j-bundle derived from INTEGRAL data by Hascoet et al. (2014). We find that a significant degeneracy appears in the inferred parameters if the footprint of the j-bundle is allowed to be a thin ring instead of a polar cap. The degeneracy is reduced when the footprint is required to be the hot spot inferred from the soft X-ray data.Comment: 14 pages, 8 figures, 4 tables. Accepted for publication in Ap

Research on Present Situation and Development Countermeasures of Art and Physical Education of Primary and Middle Schools in Sichuan’s Tibetan Area

Art and physical education can promote students’ physical quality, the shaping of personality and so on. With development and improvement of modern quality education, colleges and universities at all levels are continuously promoting their attention to art and physical education. Because the limitation from many ways such as regional development, economic conditions, etc., art and physical education’s quality of primary and middle schools in Sichuan’s Tibetan area hasn’t been improved effectively. So this article mainly with present situations of art and physical education in primary and middle schools in Sichuan’s Tibetan area as research object, hopes to find out its problems and development countermeasures by author’s effort to promote its continuous improvement

Fault detection in model predictive controller

Real-time monitoring and maintaining model predictive controller (MPC) is becoming an important issue with its wide implementation in the industries. In this paper, a measure is proposed to detect faults in MPCs by comparing the performance of the actual 'controller with the pedormance of the ideal controller. The ideal controller is derived from the dynamic matrix control @MC) in an ideal work situation and treated as a measure benchmark. A detection index based on the comparison is proposed to detect the state change of the target controller. This measure is illustrated through the implementation for a water tank process

Maintaining control performance in faulty control systems

Controller failures degrade a control system pedormance. In this paper, a novel main fenonce approach for controllerfailures is proposed fo restore fhe degraded peformance of the controller. The method is fo equivolenfly shifr any foulf occurring in a controller to the plant. Eased on the assumed process model, a compensafor with a serial link is designed to nlainfain the faulty controller in the SISO and MMO control systems. Several simulafioir results are given fo illustrate the procedure of using the metho

Combat Network Synchronization of UCAV Formation Based on RTBA Model

The paper aims at developing an efficient method to acquire a proper UCAV formation structure with robust and synchronized features. Here we introduce the RTBA (Route Temporary Blindness Avoidance) model to keep the structure stable and the HPSO (hybrid particle swarm optimization) method is given to find an optimal synchronized formation. The major contributions include the following: (1) setting up the dynamic hierarchy topologic structure of UCAV formation; (2) the RTB phenomenon is described and the RTBA model is put forward; (3) the node choosing rules are used to keep the invulnerability of the formation and the detective information quantifying method is given to measure the effectiveness of the connected nodes; and (4) the hybrid particle swarm optimization method is given to find an optimal synchronized topologic structure. According to the related principles and models, the simulations are given in the end, and the results show that the simplification of the model is available in engineering, and the RTBA model is useful to solve the real problems in combat in some degree

Terminal Guidance Law for UAV Based on Receding Horizon Control Strategy

Terminal guidance law against the maneuvering target is always the focal point. Most of the literatures focus on estimating the acceleration of target and time to go in guidance law, which are difficult to acquire. This paper presents a terminal guidance law based on receding horizon control strategy. The proposed guidance law adopts the basic framework of receding horizon control, and the guidance process is divided into several finite time horizons. Then, optimal control theory and target motion prediction model are used to derive guidance law for minimum time index function with continuous renewal of original conditions at the initial time of each horizon. Finally, guidance law performs repeated iteration until intercepting the target. The guidance law is of subprime optimal type, requiring less guidance information, and does not need to estimate the acceleration of target and time to go. Numerical simulation has verified that the proposed guidance law is more effective than traditional methods on constant and sinusoidal target with bounded acceleration

Improving Continual Relation Extraction through Prototypical Contrastive Learning

Continual relation extraction (CRE) aims to extract relations towards the continuous and iterative arrival of new data, of which the major challenge is the catastrophic forgetting of old tasks. In order to alleviate this critical problem for enhanced CRE performance, we propose a novel Continual Relation Extraction framework with Contrastive Learning, namely CRECL, which is built with a classification network and a prototypical contrastive network to achieve the incremental-class learning of CRE. Specifically, in the contrastive network a given instance is contrasted with the prototype of each candidate relations stored in the memory module. Such contrastive learning scheme ensures the data distributions of all tasks more distinguishable, so as to alleviate the catastrophic forgetting further. Our experiment results not only demonstrate our CRECL's advantage over the state-of-the-art baselines on two public datasets, but also verify the effectiveness of CRECL's contrastive learning on improving CRE performance

Who is the Real Hero? Measuring Developer Contribution via Multi-dimensional Data Integration

Proper incentives are important for motivating developers in open-source communities, which is crucial for maintaining the development of open-source software healthy. To provide such incentives, an accurate and objective developer contribution measurement method is needed. However, existing methods rely heavily on manual peer review, lacking objectivity and transparency. The metrics of some automated works about effort estimation use only syntax-level or even text-level information, such as changed lines of code, which lack robustness. Furthermore, some works about identifying core developers provide only a qualitative understanding without a quantitative score or have some project-specific parameters, which makes them not practical in real-world projects. To this end, we propose CValue, a multidimensional information fusion-based approach to measure developer contributions. CValue extracts both syntax and semantic information from the source code changes in four dimensions: modification amount, understandability, inter-function and intra-function impact of modification. It fuses the information to produce the contribution score for each of the commits in the projects. Experimental results show that CValue outperforms other approaches by 19.59% on 10 real-world projects with manually labeled ground truth. We validated and proved that the performance of CValue, which takes 83.39 seconds per commit, is acceptable to be applied in real-world projects. Furthermore, we performed a large-scale experiment on 174 projects and detected 2,282 developers having inflated commits. Of these, 2,050 developers did not make any syntax contribution; and 103 were identified as bots

Transaction-Oriented Dynamic Power Flow Tracing for Distribution Networks – Definition and Implementation in GIS Environment

There is a growing interest from owners of distributed energy resources (DERs) to actively participate in the energy market through peer-to-peer (P2P) energy trading. Many strategies have been proposed to base P2P energy trading on. However, in those schemes neither the costs of assets usage nor the losses incurred are so far taken into account. This article presents a transaction-oriented dynamic power flow tracing (PFT) platform for distribution networks (DNs) implemented in a geographic information system (GIS) environment. It introduces a new transaction model that quantifies the use of the DN, apportions the losses and unlocks a flexible use of the surplus generation enabling that prosumers can adopt simultaneously different mechanisms for participation in energy trading, maximizing renewable energy usage. The platform is also helpful for future distribution system operators (DSOs) to overcome the status invisibility of low voltage (LV) DNs, determine who makes use of the assets, debit the losses on them and explore the effects from new connections. A case study is conducted over the IEEE European LV Test Feeder. The tool provides a clear, intuitive, temporal and spatial assessment of the network operation and the resulting power transactions, including losses share and efficiency of DERs

NuSTAR Observations of the State Transition of Millisecond Pulsar Binary PSR J1023+0038

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